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40 results on '"HSV model"'

1. Active vision enhancement of new media images based on semi supervised feature fusion algorithm.

Author

Liu, Dan

Abstract

In order to improve the image visual effect, a new media image active vision enhancement method based on semi supervised feature fusion algorithm is proposed. Firstly, the image feature extraction is carried out from the three perspectives of color feature, texture feature and image subject feature. The image feature is projected into the single image model, the regularization framework is established, and the multiple graphical model based on semi supervised learning method is constructed to complete the image feature fusion and determine the image enhancement strength. HSV model is introduced to decompose the image into three channel components of H, S and V. Through the adaptive component adjustment of the three channels and RBG color space conversion, the active visual enhancement of the image is achieved. The test results show that the proposed method effectively avoids the overexposure and local distortion of the image, and retains the clarity of image details to the greatest extent. The overall quality of the enhanced image is high. [ABSTRACT FROM AUTHOR]

Published
2024
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3. Vehicle Detection Technology Based on HSV Color Model and Edge Detection

Author

Yu, Mengqi, Liu, Pengxiang, Gao, Zihuan, Li, Heng, Peng, Hui, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, You, Peng, editor, Li, Heng, editor, and Chen, Zhenxiang, editor

Published
2023
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5. Robotic System for Blood Serum Aliquoting Based on a Neural Network Model of Machine Vision.

Author

Khalapyan, Sergey, Rybak, Larisa, Nebolsin, Vasiliy, Malyshev, Dmitry, Nozdracheva, Anna, Semenenko, Tatyana, and Gavrilov, Dmitry

Subjects
COMPUTER vision, CONVOLUTIONAL neural networks, ROBOTICS, INDUSTRIAL robots, PYTHON programming language, LOW vision
Abstract

The quality of the diagnostic information obtained in the course of laboratory studies depends on the accuracy of compliance with the regulations for the necessary work. The process of aliquoting blood serum requires immersing the pipette to different depths depending on the boundary level between blood phases. A vision system can be used to determine this depth during automated aliquoting using various algorithms. As part of the work, two recognition algorithms are synthesized, one of which is based on the use of the HSV color palette, the other is based on the convolutional neural network. In the Python language, software systems have been developed that implement the ability of a vision system to recognize blood in test tubes. The developed methods are supposed to be used for aliquoting biosamples using a delta robot in a multirobotic system, which will increase the productivity of ongoing biomedical research through the use of new technical solutions and principles of intelligent robotics. The visualized results of the work of the considered programs are presented and a comparative analysis of the quality of recognition is carried out. [ABSTRACT FROM AUTHOR]

Published
2023
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6. Shot Segmentation Algorithm Based on HSV Model in Sport Video

Author

Yan, Kun, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Sugumaran, Vijayan, editor, Xu, Zheng, editor, and Zhou, Huiyu, editor

Published
2021
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7. Rapid and semi-quantitative colorimetric loop-mediated isothermal amplification detection of ASFV via HSV color model transformation

Author

Ling-Shan Yu, Sheng-Yeh Chou, Hsing-Yu Wu, Yu-Cheng Chen, and Yen-Hsu Chen

Subjects
ASFV, LAMP, Colorimetric assay, HSV model, Microbiology, QR1-502
Abstract

Background: African Swine Fever (ASF) is a highly contagious and lethal viral disease of swine, the presence of which in groups of pigs leads to enormous economic losses in the farming industry. However, vaccines and drugs to treat ASF have yet to be developed. To control the spread of the African Swine Fever Virus (ASFV), a diagnostic method that can be applied rapidly and can detect the disease during the early stages of infection is urgently needed. Methods: In this study, we demonstrate a rapid and easy-to-use ASFV detection method that combines loop-mediated isothermal amplification (LAMP) and image processing with the hue-saturation-value (HSV) color model. This method was validated through use of synthetic ASFV DNA. Results: The method shows high sensitivity, as it detects as few as 10 copies per reaction within 20 min. The speed and sensitivity of this newly developed assay are superior to those reported in previous studies. In addition, through HSV color space transformation, the colorimetric result of this LAMP assay can be used for a semi-quantitative analysis for ASFV (ranging from 108 to 101 copies per reaction) and improve the discern to low concentration samples from a negative control. Conclusion: These results show that the combination of ASFV-LAMP assay and HSV color space transformation may accelerate the screening process of pigs for ASFV infection. Overall, this study provides a rapid, sensitive, early-stage, on-site diagnosis of ASFV infection and has potential to be applied to other infectious diseases.

Published
2021
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8. Building Extraction Method in Remote Sensing Image

Author

Han, Qinzhe, Zheng, Xin, Yin, Qian, Chen, Ziyi, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Huang, Chuanchao, editor, Chan, Yu-Wei, editor, and Yen, Neil, editor

Published
2020
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9. Robotic System for Blood Serum Aliquoting Based on a Neural Network Model of Machine Vision

Author

Sergey Khalapyan, Larisa Rybak, Vasiliy Nebolsin, Dmitry Malyshev, Anna Nozdracheva, Tatyana Semenenko, and Dmitry Gavrilov

Subjects
automated aliquoting, blood serum, HSV model, convolutional neural network, U-Net, Mechanical engineering and machinery, TJ1-1570
Abstract

The quality of the diagnostic information obtained in the course of laboratory studies depends on the accuracy of compliance with the regulations for the necessary work. The process of aliquoting blood serum requires immersing the pipette to different depths depending on the boundary level between blood phases. A vision system can be used to determine this depth during automated aliquoting using various algorithms. As part of the work, two recognition algorithms are synthesized, one of which is based on the use of the HSV color palette, the other is based on the convolutional neural network. In the Python language, software systems have been developed that implement the ability of a vision system to recognize blood in test tubes. The developed methods are supposed to be used for aliquoting biosamples using a delta robot in a multirobotic system, which will increase the productivity of ongoing biomedical research through the use of new technical solutions and principles of intelligent robotics. The visualized results of the work of the considered programs are presented and a comparative analysis of the quality of recognition is carried out.

Published
2023
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10. HSV model based data hiding in video for watermark applications.

Author

Jerisha Liby, J. and Jaya, T

Subjects
*DIGITAL watermarking, *DATABASES, *DATA modeling
Abstract

This manuscript proposes a new data hiding approach that is used in watermark applications in video by transforming the RGB model to HSV model. This method initially estimates the number of frames needed to embed the data (watermark). Then two sets of RGB (Red, Green, Blue) coefficients (R1, G1, B1), (R2, G2, B2) are converted to HSV (Hue, saturation, values) Coefficients (H1, S1, V1) and (H2, S2, V2). The 'Value' Coefficients V1 and V2 are used to embed the watermark, since there exists a strong correlation between the adjacent 'Value' Coefficients. The same process is repeated on adjacent HSV coefficients till the watermark is fully embedded. After embedding the data HSV coefficients are again converted back to RGB coefficients. During the extraction phase, the data is extracted by transforming the RGB coefficient to HSV coefficients. One bit of information can be extracted from two adjacent HSV coefficients. Experimental outcomes show that the proposed watermarking approach is efficiently against attacks, viz noise, filtering, etc. Also, the proposed method performs better than traditional watermarking methods with the help of embedding rate (bpp), Structural similarity index measurement (SSIM), Visual quality (PSNR), Normalized cross-correlation (NC). [ABSTRACT FROM AUTHOR]

Published
2021
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11. Colorimetric detection of copper ions using porphyrin-conjugated silica nanoparticles.

Author

Singh, Baljinder, Lee, Jungmin, Kim, Hyeon-Gyu, Park, Myoung-Hwan, and Kim, Kibeom

Abstract

Objective: The importance of detection of Cu2+ metal ions has increased due to its high toxicity and wide presence in the environment. The method of sensing Cu2+ has continued to be the classic method using complex and expensive facilities. The objective of this study is to develop a simple and highly sensitive sensing method for Cu2+ detection. Methods: In this study, we have developed a simple colorimetric method for sensing Cu2+ metal ions using porphyrin-conjugated silica nanoparticles (SiNPs-Por) with high sensitivity. Porphyrin was modified on silica nanoparticles through azide-alkyne huisgen cycloaddition (click reaction), which is high yielding and simple to perform. Results: The porphyrin-based probes exhibited color change by coordination with Cu2+ metal ions at room temperature. The sensing capability of porphyrin after interacting with different concentrations of Cu2+ in solution showed variations in absorptions using UV–Vis spectroscopy and colorimetric sensing in the hue, saturation, and value model using image recognition mobile application. Conclusions: SiNPs-Por are highly responsive sensors for the detection of Cu2+. [ABSTRACT FROM AUTHOR]

Published
2020
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12. Detection of 3D points on moving objects from point cloud data for 3D modeling of outdoor environments

Author

Kanatani, Tsunetake, Kume, Hideyuki, Taketomi, Takafumi, Sato, Tomokazu, Yokoya, Naokazu, Kanatani, Tsunetake, Kume, Hideyuki, Taketomi, Takafumi, Sato, Tomokazu, and Yokoya, Naokazu

Abstract

A 3D modeling technique for an urban environment can be applied to several applications such as landscape simulations, navigational systems, and mixed reality systems. In this field, the target environment is first measured using several types of sensors (laser rangefinders, cameras, GPS sensors, and gyroscopes). A 3D model of the environment is then constructed based on the results of the 3D measurements. In this 3D modeling process, 3D points that exist on moving objects become obstacles or outliers to enable the construction of an accurate 3D model. To solve this problem, we propose a method for detecting 3D points on moving objects from 3D point cloud data based on photometric consistency and knowledge of the road environment. In our method, 3D points on moving objects are detected based on luminance variations obtained by projecting 3D points onto omnidirectional images. After detecting 3D the points based on evaluation value, the points are detected using prior information of the road environment., ICIP 2013 : 20th IEEE International Conference on Image Processing , Sep 15-18, 2013 , Melbourne, Australia

Published
2023

13. 基于LBP-HSV模型及改进SIFT算法的行人再识别算法.

Author

晋丽榕, 王海梅, and 徐丹萍

Subjects
COMPUTER engineering, ALGORITHMS, COMPUTER systems, HISTOGRAMS, SCALE invariance (Statistical physics)
Abstract

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Published
2018
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14. Building an efficient content based image retrieval system by changing the database structure

Author

Rana Jassim Mohammed, Abdulla J. Y. Aldarwish, and Ali A. Yassin

Subjects
Database, HSV model, Control and Optimization, Computer Networks and Communications, Hardware and Architecture, Signal Processing, Electrical and Electronic Engineering, Content-based image retrieval, Digital image, Information Systems
Abstract

The amount of interest in digital images is growing because of the advent of the World Wide Web. Many different industries are making use of digital images today, including medicine, design, journalism, education, and more. Images can be stored and retrieved using a variety of techniques and methods. Nevertheless, the majority of those engines are dependent on Meta data (key-words, descriptions, tags). Although efficient, costly, and able to target keywords and tags with each image, and these engines have their shortcomings. Though it may be possible to use a filtering system to give more accurate results, there are additional issues.

Published
2022

15. Classification of Sugarcane Billet Using Computer Vision

Author

Suryavanshi, Devayani, Patil, D. P., and Gunjate, S. S.

Subjects
HSV model, RGB model, Image processing, Arduino Uno, Billet
Abstract

One of the widely taken crop is sugarcane. Sugarcane is very important raw material for the production of sugar, ethanol, and bagasse. In most of countries harvesting machines are used. Recently plantation of sugarcane is done by using billets. But it has disadvantage also because when forming billets by harvesting machine it gets damaged and causes billet quality degradation and spreading of diseases. Here we developed a prototype model to classify the good and damaged billets separately. This model runs on Python program which segregate healthy (good) and damaged billets with the help of image processing technique after taking pictures of these billets using USB camera. So, the good billets goes for next planting method and remaining billets i.e. damaged billets used for sugar recovery and other by-products. &nbsp

Published
2020

16. Rapid and semi-quantitative colorimetric loop-mediated isothermal amplification detection of ASFV via HSV color model transformation

Author

Yen-Hsu Chen, Ling-Shan Yu, Yu-Cheng Chen, Hsing-Yu Wu, and Sheng-Yeh Chou

Subjects
Microbiology (medical), Diagnostic methods, Swine, Loop-mediated isothermal amplification, HSL and HSV, Biology, Microbiology, African swine fever virus, Sensitivity and Specificity, HSV model, LAMP, Immunology and Allergy, Animals, Computer Simulation, African Swine Fever, General Immunology and Microbiology, Hsv color model, General Medicine, biology.organism_classification, Virology, African Swine Fever Virus, QR1-502, Colorimetric assay, Transformation (genetics), Infectious Diseases, Molecular Diagnostic Techniques, DNA, Viral, Capsid Proteins, Colorimetry, Viral disease, ASFV, Semi quantitative, Nucleic Acid Amplification Techniques, Cell Phone
Abstract

Background African Swine Fever (ASF) is a highly contagious and lethal viral disease of swine, the presence of which in groups of pigs leads to enormous economic losses in the farming industry. However, vaccines and drugs to treat ASF have yet to be developed. To control the spread of the African Swine Fever Virus (ASFV), a diagnostic method that can be applied rapidly and can detect the disease during the early stages of infection is urgently needed. Methods In this study, we demonstrate a rapid and easy-to-use ASFV detection method that combines loop-mediated isothermal amplification (LAMP) and image processing with the hue-saturation-value (HSV) color model. This method was validated through use of synthetic ASFV DNA. Results The method shows high sensitivity, as it detects as few as 10 copies per reaction within 20 min. The speed and sensitivity of this newly developed assay are superior to those reported in previous studies. In addition, through HSV color space transformation, the colorimetric result of this LAMP assay can be used for a semi-quantitative analysis for ASFV (ranging from 108 to 101 copies per reaction) and improve the discern to low concentration samples from a negative control. Conclusion These results show that the combination of ASFV-LAMP assay and HSV color space transformation may accelerate the screening process of pigs for ASFV infection. Overall, this study provides a rapid, sensitive, early-stage, on-site diagnosis of ASFV infection and has potential to be applied to other infectious diseases.

Published
2020

17. Traffic signs and signals detection employing the MY VISION system for a visually impaired person

Author

Graduate School of Engineering, Kyushu Institute of Technology, Sensuicho 1-1, Tobata, Kitakyushu, Fukuoka 804-8550, Japan, Faculty of Engineering, Kyushu Institute of Technology, Sensuicho 1-1, Tobata, Kitakyushu, Fukuoka 804-8550, Japan, Kumano, Takaki, Tan, Joo Kooi, Kim, Hyoungseop, Ishikawa, Seiji, Graduate School of Engineering, Kyushu Institute of Technology, Sensuicho 1-1, Tobata, Kitakyushu, Fukuoka 804-8550, Japan, Faculty of Engineering, Kyushu Institute of Technology, Sensuicho 1-1, Tobata, Kitakyushu, Fukuoka 804-8550, Japan, Kumano, Takaki, Tan, Joo Kooi, Kim, Hyoungseop, and Ishikawa, Seiji

Abstract

type:Journal Article, In recent years, the equipment on walk support for visually impaired persons has spread to a certain extent. A studded paving block and a sound-type signal are set on the sidewalk or on the road in many places. However, there are still problems such that the studded paving block is still installed at limited places, or the sound of the signal is obscure because of the environmental noise such as roaring traffic or heavy rain. Therefore, a system that can support visually impaired persons in more effective way is necessary, such as a system which finds a signal or a traffic sign automatically and provides its information to the visually impaired. In order to realize such a system, this paper proposes a method of detecting pedestrian signals and crosswalk signs by a camera and a computer which we call MY VISION system. In the proposed method, color information is used in the first step to restrict the search for traffic signal and sign candidates, and then the HOG feature is introduced to describe the candidates by feature vectors. Recognition of the signals and the signs is performed by applying randomized trees to the candidates. The color sign of the pedestrian signal is also discriminated by using color information.Experimental results are shown and the method is evaluated.

Published
2020

18. Deep inside the color: How optical microscopy contributes to the elemental characterization of a painting

Author

Galli, A, Caccia, M, Bonizzoni, L, Gargano, M, Ludwig, N, Poldi, G, Martini, M, Galli A., Caccia M., Bonizzoni L., Gargano M., Ludwig N., Poldi G., Martini M., Galli, A, Caccia, M, Bonizzoni, L, Gargano, M, Ludwig, N, Poldi, G, Martini, M, Galli A., Caccia M., Bonizzoni L., Gargano M., Ludwig N., Poldi G., and Martini M.

Abstract

In the context of paintings characterization, X-Ray Fluorescence (XRF) combined with Fibre Optics Reflectance Spectroscopy (FORS) is a well-known methodology. The latter allows to classify the pigments constituting the external layers (few microns) of the painting while the former provides the fingerprint of the main chemical elements present in almost all layers (tens of microns) of the sample. The synergetic application of XRF and FORS is a key turn for non-invasive scientific analysis of works of art since it exhaustively describes the pigments employed by the masters and supplies a first insight into their distribution on the panels. In this scenario, Optical Microscopy (OM) applied directly on the painting surface, without any type of sampling, is traditionally deemed as a descriptive tool for showing microscopic features such as craquelure, brushstrokes or painting material distribution. It can be eventually expendable as a qualitative help during the discussion of spectroscopic data, but not considered fundamental. Nonetheless, the application of image processing protocols can make OM a concrete support for the characterization of paintings. In this work a new image analysis strategy has been introduced, its potential has been demonstrated studying different flesh tones from the panel “The Holy Family with St. Anne and the young St. John” by Bernardino Luini (Pinacoteca Ambrosiana Collection of Milan) and, finally, it has been discussed how OM could quantitatively complete XRF and FORS analysis. The results show that optical microscopy, other than provide a glance of the investigated surface spots, effectively integrates the description given by the spectroscopic techniques and, properly managed, can be a useful resource for solving ambiguous cases.

Published
2020

19. Deep inside the color: How optical microscopy contributes to the elemental characterization of a painting

Author

Marco Gargano, Michele Caccia, Letizia Bonizzoni, Anna Galli, Marco Martini, Gianluca Poldi, Nicola Ludwig, Galli, A, Caccia, M, Bonizzoni, L, Gargano, M, Ludwig, N, Poldi, G, and Martini, M

Subjects
Pigments, Computer science, Sample (material), Reflectance spectroscopy, XRF, Image processing, Context (language use), 02 engineering and technology, Optical microscopy, 01 natural sciences, Analytical Chemistry, law.invention, HSV model, Optical microscope, law, Computer graphics (images), Spectroscopy, FORS, Painting, Multivariate representation, 010401 analytical chemistry, 021001 nanoscience & nanotechnology, 0104 chemical sciences, Characterization (materials science), Pigment, Material distribution, 0210 nano-technology
Abstract

In the context of paintings characterization, X-Ray Fluorescence (XRF) combined with Fibre Optics Reflectance Spectroscopy (FORS) is a well-known methodology. The latter allows to classify the pigments constituting the external layers (few microns) of the painting while the former provides the fingerprint of the main chemical elements present in almost all layers (tens of microns) of the sample. The synergetic application of XRF and FORS is a key turn for non-invasive scientific analysis of works of art since it exhaustively describes the pigments employed by the masters and supplies a first insight into their distribution on the panels. In this scenario, Optical Microscopy (OM) applied directly on the painting surface, without any type of sampling, is traditionally deemed as a descriptive tool for showing microscopic features such as craquelure, brushstrokes or painting material distribution. It can be eventually expendable as a qualitative help during the discussion of spectroscopic data, but not considered fundamental. Nonetheless, the application of image processing protocols can make OM a concrete support for the characterization of paintings. In this work a new image analysis strategy has been introduced, its potential has been demonstrated studying different flesh tones from the panel “The Holy Family with St. Anne and the young St. John” by Bernardino Luini (Pinacoteca Ambrosiana Collection of Milan) and, finally, it has been discussed how OM could quantitatively complete XRF and FORS analysis. The results show that optical microscopy, other than provide a glance of the investigated surface spots, effectively integrates the description given by the spectroscopic techniques and, properly managed, can be a useful resource for solving ambiguous cases.

Published
2020
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20. TRAFFIC SIGNS AND SIGNALS DETECTION EMPLOYING THE MY VISION SYSTEM FOR A VISUALLY IMPAIRED PERSON

Author

Kumano, Takaki, Tan, Joo Kooi, Kim, Hyoungseop, and Ishikawa, Seiji

Subjects
HSV model, HOG, MY VISION, Randomized trees, Computer vision
Abstract

In recent years, the equipment on walk support for visually impaired persons has spread to a certain extent. A studded paving block and a sound-type signal are set on the sidewalk or on the road in many places. However, there are still problems such that the studded paving block is still installed at limited places, or the sound of the signal is obscure because of the environmental noise such as roaring traffic or heavy rain. Therefore, a system that can support visually impaired persons in more effective way is necessary, such as a system which finds a signal or a traffic sign automatically and provides its information to the visually impaired. In order to realize such a system, this paper proposes a method of detecting pedestrian signals and crosswalk signs by a camera and a computer which we call MY VISION system. In the proposed method, color information is used in the first step to restrict the search for traffic signal and sign candidates, and then the HOG feature is introduced to describe the candidates by feature vectors. Recognition of the signals and the signs is performed by applying randomized trees to the candidates. The color sign of the pedestrian signal is also discriminated by using color information.Experimental results are shown and the method is evaluated.

Published
2016

21. An Adaptive Vision-based Sensor for Underwater Line Detection Employing Shape and Color Image Segmentation

Author

Jordan, Mario Alberto and Trabes, Emanuel

Subjects
HSV model, optimal parameter adjustments, underwater pipeline detection, purl.org/becyt/ford/2 [https], adaptative sensor, chanching illumination levels, Control Automático y Robótica, INGENIERÍAS Y TECNOLOGÍAS, purl.org/becyt/ford/2.2 [https], Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información, vision-based sensor
Abstract

This work aims the design and implementation of an adaptive vision-based sensor for detecting a pipe on underwater scenes in real time. The motivation is focused to future applications of vision servo control in underwater vehicles. The approach employs color and shape image segmentation together with an adjust mechanism that aims continuously in time to reach the best setup of a parameter set of the color image segmentation. The sensor performs very well even in the case of large and rapid changes in the scene illumination. On the basis of many experiments carried out in real scenes and the comparison with similar algorithms in the state-of-the-art field on the same application, the approach gets a better positioning with respect to related results above all in the case of extremely changing and poor luminance conditions. As drawback, the required computation time to achieve optimal values for the first time (auto-tuning phase) may be large; contrary to the adaptive ongoing process, in where the optimization is much more agile. Fil: Jordan, Mario Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina. Universidad Nacional del Sur. Departamento de Ingenieria Electrica y de Computadoras; Argentina Fil: Trabes, Emanuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Bahía Blanca. Instituto Argentino de Oceanografía (i); Argentina

Published
2015

22. Image Processing Using Color and Object Information for Wireless Capsule Endoscopy

Author

Park, Jin-Hee, Yong-Gyu Lee, and Gilwon Yoon

Subjects
HSV model, genetic structures, Image processing, Object Identification, Capsule Endoscopy, Color Separation
Abstract

Wireless capsule endoscopy provides real-time images in the digestive tract. Capsule images are usually low resolution and are diverse images due to travel through various regions of human body. Color information has been a primary reference in predicting abnormalities such as bleeding. Often color is not sufficient for this purpose. In this study, we took morphological shapes into account as additional, but important criterion. First, we processed gastric images in order to indentify various objects in the image. Then, we analyzed color information in the object. In this way, we could remove unnecessary information and increase the accuracy. Compared to our previous investigations, we could handle images of various degrees of brightness and improve our diagnostic algorithm., {"references":["","A. Mata, J. Llach, and JM. Bordas, \"Wireless Capsule Endoscopy,\"\nWorld J Gastroenterol, April 7, 2008, Vol. 14, no.13, pp. 1969 -1971.","A. Glukhovsky, \"Wireless capsule endoscopy\", Sensor Review, vol. 23,\nno. 2, 2003, pp. 128–133.","D. G. Adler and C. J. Gostout, \"Wireless Capsule Endoscopy\", Hospital\nPhysician, 2003, pp.14-22.","Y.-G. Lee, and G. Yoon, \"Bleeding Detection Algorithm for Capsule\nEndoscopy,\" World academy of science engineering and technology, vol.\n81, pp. 672-677, Sem., 2011.","Y.-G. Lee, and G. Yoon, \"Real-Time Image Analysis of Capsule\nEndoscopy for Bleeding Discrimination in Embedded System Platform,\"\nWorld academy of science engineering and technology, vol. 59, pp.\n2526-2530, Dec., 2011.","Y.-G. Lee, and G. Yoon, \"Improvement of Blood Detection Accuracy\nusing Image Processing Techniques suitable for Capsule Endoscopy,\"\nWorld academy of science engineering and technology, vol. 65, pp.\n1096-1099, May, 2012.","Tony Lindeberg, \"Edge Detection and Ridge Detection with Automatic\nScale Selection,\" International J of Computer Vision, Nov, 1998, vol. 30,\nno. 2, pp. 117-156.","Heath, M. D., Sarkar, S., Sanocki, T., Bowyer, K. W., \"A robust visual\nmethod for assessing the relative performance of edge-detection\nalgorithms,\" IEEE Trans on Pattern Analysis and Machine Intelligence,\nvol. 19, no. 12, pp. 1338-1359, Dec, 1997.","F Catté, PL Lions, JM Morel, T Coll, \"Image Selective Smoothing and\nEdge Detection by Nonlinear Diffusion,\" SIAM Journal on Numerical\nAnalysis, vol. 29, no.1, pp. 182-193, Feb, 1992\n[10] JH Elder, SW Zucker, \"Local scale control for edge detection and blur\nestimation,\" IEEE Trans on Pattern Analysis and Machine Intelligence,\nvol. 20, no. 7, pp. 699-715, Jul, 1998.\n[11] J. F. Canny, \"A Computational Approach to Edge Detection,\" IEEE\nTrans. Pattern Analysis and Machine intelligence, vol. PAMI-8, no. 6,\npp. 679–698, Nov. 1986."]}

Published
2013
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23. Detection of 3D points on moving objects from point cloud data for 3D modeling of outdoor environments

Author

Takafumi Taketomi, Tsunetake Kanatani, Naokazu Yokoya, Hideyuki Kume, and Tomokazu Sato

Subjects
Computer science, solid modelling, omnidirectional images, outdoor environment 3D modeling, Point cloud, laser ranging, gyroscopes, image motion analysis, 3D points projection, GPS sensors, Luminance, computer vision, 3D Point Cloud Data, Global Positioning System, cameras, navigational system, point cloud data, 3D Modeling, 3D point detection, laser rangefinders, Computer vision, Moving Objects, sensor fusion, 3D measurement, photometric consistency, business.industry, mixed reality system, outliers, Process (computing), road environment, object detection, 3D modeling, Sensor fusion, obstacles, urban environment, Mixed reality, Object detection, luminance variation, landscape simulation, HSV Model, Artificial intelligence, business, Outdoor Environment
Abstract

A 3D modeling technique for an urban environment can be applied to several applications such as landscape simulations, navigational systems, and mixed reality systems. In this field, the target environment is first measured using several types of sensors (laser rangefinders, cameras, GPS sensors, and gyroscopes). A 3D model of the environment is then constructed based on the results of the 3D measurements. In this 3D modeling process, 3D points that exist on moving objects become obstacles or outliers to enable the construction of an accurate 3D model. To solve this problem, we propose a method for detecting 3D points on moving objects from 3D point cloud data based on photometric consistency and knowledge of the road environment. In our method, 3D points on moving objects are detected based on luminance variations obtained by projecting 3D points onto omnidirectional images. After detecting 3D the points based on evaluation value, the points are detected using prior information of the road environment., ICIP 2013 : 20th IEEE International Conference on Image Processing , Sep 15-18, 2013 , Melbourne, Australia

Published
2013

24. Detection of 3D points on moving objects from point cloud data for 3D modeling of outdoor environments

Author

Kanatani, Tsunetake, Kume, Hideyuki, 50610664, Taketomi, Takafumi, 50362835, Sato, Tomokazu, 10252834, Yokoya, Naokazu, Kanatani, Tsunetake, Kume, Hideyuki, 50610664, Taketomi, Takafumi, 50362835, Sato, Tomokazu, 10252834, and Yokoya, Naokazu

Abstract

application/pdf, A 3D modeling technique for an urban environment can be applied to several applications such as landscape simulations, navigational systems, and mixed reality systems. In this field, the target environment is first measured using several types of sensors (laser rangefinders, cameras, GPS sensors, and gyroscopes). A 3D model of the environment is then constructed based on the results of the 3D measurements. In this 3D modeling process, 3D points that exist on moving objects become obstacles or outliers to enable the construction of an accurate 3D model. To solve this problem, we propose a method for detecting 3D points on moving objects from 3D point cloud data based on photometric consistency and knowledge of the road environment. In our method, 3D points on moving objects are detected based on luminance variations obtained by projecting 3D points onto omnidirectional images. After detecting 3D the points based on evaluation value, the points are detected using prior information of the road environment.

Published
2013

25. Sledování objektů kamerou

Author

Rozman, Jaroslav, Orság, Filip, Psota, Michal, Rozman, Jaroslav, Orság, Filip, and Psota, Michal

Abstract

Tato práce se zabývá teoretickým popisem, návrhem a implementací programu pro sledování barevných objektů pomocí robota. Při zpracování obrazu je použit wrapper knihovny OpenCV - EmguCV. Aplikace komunikuje s robotem a navádí jej tak, aby sledoval zadaný barevný objekt. Program je implementován v jazyce C#, This work focuses on theoretical description, proposal and implementation of a program for coloured object tracking by a robot. Picture processing uses wrapper of OpenCV library - EmguCV. The application communicates with the robot and guides it to track a specified coloured object. The program is implemented in C# language.

26. Detection, Extraction and Measurement of the Length and Width of the Metacarpal Bones in Images

Author

Drahanský, Martin, Dvořák, Michal, Paul, Daniel, Drahanský, Martin, Dvořák, Michal, and Paul, Daniel

Abstract

Ľudské telo bolo po celé storočia bodom mnohých štúdií. Chceme zistiť všetko, čo je možné sa o nás dozvedieť, o tom, ako fungujeme a prečo tak fungujeme. Vedci nám poskytujú výskumy, ktoré objasňujú tieto otázky. Mali by sme byť súčasťou tohto výskumu a obohatiť naše vedomosti prispievaním do vedy. Preto bude táto práca zameraná na detekciu, extrakciu a meranie metakarpálnych kostí na obrázkoch. Táto práca poskytne čitateľovi vedomosti o určitých metódach spracovania obrazu a záprstných kostiach. Predstaví proces extrakcie ich kontúr a ukáže spôsob, ako merať ich šírku a výšku., A human body has been a point of the many studies for centuries. We want to discover everything there is to know about us, how we function and why we function that way. Scientists provide us with research that clarifies these questions. We should be a part for this research and enrich our knowledge with contribution to science. That's why this work will be focused on detecting, extracting and measuring metacarpal bones in images. The work will provide the reader with knowledge about certain image processing methods and metacarpal bones. It will introduce process of extracting their contour and show a way to measure their width and height.

27. Detection, Extraction and Measurement of the Length and Width of the Metacarpal Bones in Images

Author

Drahanský, Martin, Dvořák, Michal, Paul, Daniel, Drahanský, Martin, Dvořák, Michal, and Paul, Daniel

Abstract

Ľudské telo bolo po celé storočia bodom mnohých štúdií. Chceme zistiť všetko, čo je možné sa o nás dozvedieť, o tom, ako fungujeme a prečo tak fungujeme. Vedci nám poskytujú výskumy, ktoré objasňujú tieto otázky. Mali by sme byť súčasťou tohto výskumu a obohatiť naše vedomosti prispievaním do vedy. Preto bude táto práca zameraná na detekciu, extrakciu a meranie metakarpálnych kostí na obrázkoch. Táto práca poskytne čitateľovi vedomosti o určitých metódach spracovania obrazu a záprstných kostiach. Predstaví proces extrakcie ich kontúr a ukáže spôsob, ako merať ich šírku a výšku., A human body has been a point of the many studies for centuries. We want to discover everything there is to know about us, how we function and why we function that way. Scientists provide us with research that clarifies these questions. We should be a part for this research and enrich our knowledge with contribution to science. That's why this work will be focused on detecting, extracting and measuring metacarpal bones in images. The work will provide the reader with knowledge about certain image processing methods and metacarpal bones. It will introduce process of extracting their contour and show a way to measure their width and height.

28. Rozpoznání dopravních značek využitím neuronové sítě

Author

Jirsík, Václav, Horák, Karel, Zámečník, Dušan, Jirsík, Václav, Horák, Karel, and Zámečník, Dušan

Abstract

Práca sa zoberá rozpoznávaním červených dopravných značiek. Je využitá segmentácia červenej farby v HSV modeli. Na klasifikáciu využívam kombináciu niektorých vybraných rádiometrických príznakov, príznakov z Houghovej transformácie a jednoduchých natrénovaných neurónových sietí. V závere je navrhnutý komplexný rozhodovací algoritmus., This paper deals with traffic signs recognition. Red color area is obtained by thresholding in HSV color model. Selected radiometric deskriptors, Hough transform deskriptors and neural networs are used to classification. In conclusion has been designed complex decision algorithm.

29. Sledování objektů kamerou

Author

Rozman, Jaroslav, Orság, Filip, Psota, Michal, Rozman, Jaroslav, Orság, Filip, and Psota, Michal

Abstract

Tato práce se zabývá teoretickým popisem, návrhem a implementací programu pro sledování barevných objektů pomocí robota. Při zpracování obrazu je použit wrapper knihovny OpenCV - EmguCV. Aplikace komunikuje s robotem a navádí jej tak, aby sledoval zadaný barevný objekt. Program je implementován v jazyce C#, This work focuses on theoretical description, proposal and implementation of a program for coloured object tracking by a robot. Picture processing uses wrapper of OpenCV library - EmguCV. The application communicates with the robot and guides it to track a specified coloured object. The program is implemented in C# language.

30. Rozpoznání dopravních značek využitím neuronové sítě

Author

Jirsík, Václav, Horák, Karel, Jirsík, Václav, and Horák, Karel

Abstract

Práca sa zoberá rozpoznávaním červených dopravných značiek. Je využitá segmentácia červenej farby v HSV modeli. Na klasifikáciu využívam kombináciu niektorých vybraných rádiometrických príznakov, príznakov z Houghovej transformácie a jednoduchých natrénovaných neurónových sietí. V závere je navrhnutý komplexný rozhodovací algoritmus., This paper deals with traffic signs recognition. Red color area is obtained by thresholding in HSV color model. Selected radiometric deskriptors, Hough transform deskriptors and neural networs are used to classification. In conclusion has been designed complex decision algorithm.

31. Sledování objektů kamerou

Author

Rozman, Jaroslav, Orság, Filip, Rozman, Jaroslav, and Orság, Filip

Abstract

Tato práce se zabývá teoretickým popisem, návrhem a implementací programu pro sledování barevných objektů pomocí robota. Při zpracování obrazu je použit wrapper knihovny OpenCV - EmguCV. Aplikace komunikuje s robotem a navádí jej tak, aby sledoval zadaný barevný objekt. Program je implementován v jazyce C#, This work focuses on theoretical description, proposal and implementation of a program for coloured object tracking by a robot. Picture processing uses wrapper of OpenCV library - EmguCV. The application communicates with the robot and guides it to track a specified coloured object. The program is implemented in C# language.

32. Sledování objektů kamerou

Author

Rozman, Jaroslav, Orság, Filip, Rozman, Jaroslav, and Orság, Filip

Abstract

Tato práce se zabývá teoretickým popisem, návrhem a implementací programu pro sledování barevných objektů pomocí robota. Při zpracování obrazu je použit wrapper knihovny OpenCV - EmguCV. Aplikace komunikuje s robotem a navádí jej tak, aby sledoval zadaný barevný objekt. Program je implementován v jazyce C#, This work focuses on theoretical description, proposal and implementation of a program for coloured object tracking by a robot. Picture processing uses wrapper of OpenCV library - EmguCV. The application communicates with the robot and guides it to track a specified coloured object. The program is implemented in C# language.

33. Rozpoznání dopravních značek využitím neuronové sítě

Author

Jirsík, Václav, Horák, Karel, Jirsík, Václav, and Horák, Karel

Abstract

Práca sa zoberá rozpoznávaním červených dopravných značiek. Je využitá segmentácia červenej farby v HSV modeli. Na klasifikáciu využívam kombináciu niektorých vybraných rádiometrických príznakov, príznakov z Houghovej transformácie a jednoduchých natrénovaných neurónových sietí. V závere je navrhnutý komplexný rozhodovací algoritmus., This paper deals with traffic signs recognition. Red color area is obtained by thresholding in HSV color model. Selected radiometric deskriptors, Hough transform deskriptors and neural networs are used to classification. In conclusion has been designed complex decision algorithm.

34. Sledování objektů kamerou

Author

Rozman, Jaroslav, Orság, Filip, Rozman, Jaroslav, and Orság, Filip

Abstract

Tato práce se zabývá teoretickým popisem, návrhem a implementací programu pro sledování barevných objektů pomocí robota. Při zpracování obrazu je použit wrapper knihovny OpenCV - EmguCV. Aplikace komunikuje s robotem a navádí jej tak, aby sledoval zadaný barevný objekt. Program je implementován v jazyce C#, This work focuses on theoretical description, proposal and implementation of a program for coloured object tracking by a robot. Picture processing uses wrapper of OpenCV library - EmguCV. The application communicates with the robot and guides it to track a specified coloured object. The program is implemented in C# language.

35. Detection, Extraction and Measurement of the Length and Width of the Metacarpal Bones in Images

Author

Drahanský, Martin, Dvořák, Michal, Drahanský, Martin, and Dvořák, Michal

Abstract

Ľudské telo bolo po celé storočia bodom mnohých štúdií. Chceme zistiť všetko, čo je možné sa o nás dozvedieť, o tom, ako fungujeme a prečo tak fungujeme. Vedci nám poskytujú výskumy, ktoré objasňujú tieto otázky. Mali by sme byť súčasťou tohto výskumu a obohatiť naše vedomosti prispievaním do vedy. Preto bude táto práca zameraná na detekciu, extrakciu a meranie metakarpálnych kostí na obrázkoch. Táto práca poskytne čitateľovi vedomosti o určitých metódach spracovania obrazu a záprstných kostiach. Predstaví proces extrakcie ich kontúr a ukáže spôsob, ako merať ich šírku a výšku., A human body has been a point of the many studies for centuries. We want to discover everything there is to know about us, how we function and why we function that way. Scientists provide us with research that clarifies these questions. We should be a part for this research and enrich our knowledge with contribution to science. That's why this work will be focused on detecting, extracting and measuring metacarpal bones in images. The work will provide the reader with knowledge about certain image processing methods and metacarpal bones. It will introduce process of extracting their contour and show a way to measure their width and height.

36. Detection, Extraction and Measurement of the Length and Width of the Metacarpal Bones in Images

Author

Drahanský, Martin, Dvořák, Michal, Drahanský, Martin, and Dvořák, Michal

Abstract

Ľudské telo bolo po celé storočia bodom mnohých štúdií. Chceme zistiť všetko, čo je možné sa o nás dozvedieť, o tom, ako fungujeme a prečo tak fungujeme. Vedci nám poskytujú výskumy, ktoré objasňujú tieto otázky. Mali by sme byť súčasťou tohto výskumu a obohatiť naše vedomosti prispievaním do vedy. Preto bude táto práca zameraná na detekciu, extrakciu a meranie metakarpálnych kostí na obrázkoch. Táto práca poskytne čitateľovi vedomosti o určitých metódach spracovania obrazu a záprstných kostiach. Predstaví proces extrakcie ich kontúr a ukáže spôsob, ako merať ich šírku a výšku., A human body has been a point of the many studies for centuries. We want to discover everything there is to know about us, how we function and why we function that way. Scientists provide us with research that clarifies these questions. We should be a part for this research and enrich our knowledge with contribution to science. That's why this work will be focused on detecting, extracting and measuring metacarpal bones in images. The work will provide the reader with knowledge about certain image processing methods and metacarpal bones. It will introduce process of extracting their contour and show a way to measure their width and height.

37. Detection, Extraction and Measurement of the Length and Width of the Metacarpal Bones in Images

Author

Drahanský, Martin, Dvořák, Michal, Drahanský, Martin, and Dvořák, Michal

Abstract

Ľudské telo bolo po celé storočia bodom mnohých štúdií. Chceme zistiť všetko, čo je možné sa o nás dozvedieť, o tom, ako fungujeme a prečo tak fungujeme. Vedci nám poskytujú výskumy, ktoré objasňujú tieto otázky. Mali by sme byť súčasťou tohto výskumu a obohatiť naše vedomosti prispievaním do vedy. Preto bude táto práca zameraná na detekciu, extrakciu a meranie metakarpálnych kostí na obrázkoch. Táto práca poskytne čitateľovi vedomosti o určitých metódach spracovania obrazu a záprstných kostiach. Predstaví proces extrakcie ich kontúr a ukáže spôsob, ako merať ich šírku a výšku., A human body has been a point of the many studies for centuries. We want to discover everything there is to know about us, how we function and why we function that way. Scientists provide us with research that clarifies these questions. We should be a part for this research and enrich our knowledge with contribution to science. That's why this work will be focused on detecting, extracting and measuring metacarpal bones in images. The work will provide the reader with knowledge about certain image processing methods and metacarpal bones. It will introduce process of extracting their contour and show a way to measure their width and height.

38. Rozpoznání dopravních značek využitím neuronové sítě

Author

Jirsík, Václav, Horák, Karel, Jirsík, Václav, and Horák, Karel

Abstract

Práca sa zoberá rozpoznávaním červených dopravných značiek. Je využitá segmentácia červenej farby v HSV modeli. Na klasifikáciu využívam kombináciu niektorých vybraných rádiometrických príznakov, príznakov z Houghovej transformácie a jednoduchých natrénovaných neurónových sietí. V závere je navrhnutý komplexný rozhodovací algoritmus., This paper deals with traffic signs recognition. Red color area is obtained by thresholding in HSV color model. Selected radiometric deskriptors, Hough transform deskriptors and neural networs are used to classification. In conclusion has been designed complex decision algorithm.

39. Rozpoznání dopravních značek využitím neuronové sítě

Author

Jirsík, Václav, Horák, Karel, Zámečník, Dušan, Jirsík, Václav, Horák, Karel, and Zámečník, Dušan

Abstract

Práca sa zoberá rozpoznávaním červených dopravných značiek. Je využitá segmentácia červenej farby v HSV modeli. Na klasifikáciu využívam kombináciu niektorých vybraných rádiometrických príznakov, príznakov z Houghovej transformácie a jednoduchých natrénovaných neurónových sietí. V závere je navrhnutý komplexný rozhodovací algoritmus., This paper deals with traffic signs recognition. Red color area is obtained by thresholding in HSV color model. Selected radiometric deskriptors, Hough transform deskriptors and neural networs are used to classification. In conclusion has been designed complex decision algorithm.

40. Detection, Extraction and Measurement of the Length and Width of the Metacarpal Bones in Images

Author

Drahanský, Martin, Dvořák, Michal, Paul, Daniel, Drahanský, Martin, Dvořák, Michal, and Paul, Daniel

Abstract

Ľudské telo bolo po celé storočia bodom mnohých štúdií. Chceme zistiť všetko, čo je možné sa o nás dozvedieť, o tom, ako fungujeme a prečo tak fungujeme. Vedci nám poskytujú výskumy, ktoré objasňujú tieto otázky. Mali by sme byť súčasťou tohto výskumu a obohatiť naše vedomosti prispievaním do vedy. Preto bude táto práca zameraná na detekciu, extrakciu a meranie metakarpálnych kostí na obrázkoch. Táto práca poskytne čitateľovi vedomosti o určitých metódach spracovania obrazu a záprstných kostiach. Predstaví proces extrakcie ich kontúr a ukáže spôsob, ako merať ich šírku a výšku., A human body has been a point of the many studies for centuries. We want to discover everything there is to know about us, how we function and why we function that way. Scientists provide us with research that clarifies these questions. We should be a part for this research and enrich our knowledge with contribution to science. That's why this work will be focused on detecting, extracting and measuring metacarpal bones in images. The work will provide the reader with knowledge about certain image processing methods and metacarpal bones. It will introduce process of extracting their contour and show a way to measure their width and height.

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