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Digital images increasingly determine the way people interact with physical space. Combined imaging and sensing technologies register, process, and transmit information about the physical world in real time and make it possible to continuously adapt such images to specific spatio-temporal settings and in relation to motion and perspective. With the ability to integrate situative and customised information in media, like digital maps or virtual reality applications, images also gain in importance for perception and interpretation. Such integration of image, action, and space heralds a new type of visual media described as adaptive images. Based on cases from industrial production, medicine, and psychotherapy as well as from sports and entertainment, the paper addresses their aesthetic, spatial, and operational conditions, and provides a typological survey of adaptive images as a phenomenon, including their respective challenges and implications for image and media theory.

Segmentation is one of the latest directions of digital imaging development, presented by partial segments which are parts of the same image. The currently used algorithms are rare and far from ideal. Depending on the situation, algorithms behave differently, so it is almost impossible to single out a unique conclusion. This paper gives a proposal for new segmentation techniques with the help of Imaging Biomarkers for the digital image processing with auxiliary Hybrid edge detection algorithm and especially a defined threshold of detection. Matlab software is used for giving a particular conceptual design of a partial display of images and for correlating adequate numerical methods of digital processing. The study results confirm the quality of the proposed algorithm and position it for practical use in classification of BI-RADS breasts classified by density.

Multimedia files play an important role in everyday life. Today, the majority of the population owns state-of-the-art cameras integrated into their mobile devices. Technological development not only facilitates the generation of multimedia content, but also the intentional manipulation of it, and this is where forensic techniques of detecting manipulation on images and videos take on great importance. Although historically there has been confidence in the integrity of images, the advance of technology has begun to erode this confidence. This work proposes a digital image authentication method based on the quadratic mean error of the Color Filter Array interpolation pattern estimated from the analysed image. For the evaluation of the proposed method, experiments were carried out with public databases of forged images that are widely developed for research purposes. The results of the experiments demonstrate the efficiency of the proposed method.

The paper deals with the reconstruction of implicitly defined functions or digital images. Functions are defined using observations, each of which is the result of a pairwise comparison of the function values for two random arguments. The analysis of the current state of research for particular statements of this problem is presented: the method of pairwise comparisons used in decision-making for a finite set of alternatives; reconstruction of preference/utility function in multicriteria tasks; sign representations of images used for the description and analysis of digital images. A unified approach to reconstructing functions and images according to their sign representations is proposed, based on mapping in a high-dimensional space and constructing a linear (when reconstructing a function and images) or non-linear (including non-parametric) classifier (when reconstructing preferences). For a number of classification algorithms, experimental studies have been conducted to evaluate the effectiveness of the proposed approach using the example of the reconstruction of the utility function in problems of decision theory and reconstruction of the brightness function of real images.

Maraknya kasus pencurian data menyebabkan sistem keamanan pesan harus ditingkatkan. Salah satu cara untuk mengamankan pesan adalah dengan memasukkan pesan ke dalam gambar digital. Penelitian ini bertujuan untuk meningkatkan kualitas gambar digital dalam sistem keamanan pesan tersembunyi. Teknik yang digunakan untuk keamanan pesan adalah steganografi. Cover image akan dikonversi menjadi bit piksel dalam domain spasial. Cover image digunakan dalam bentuk gambar digital dengan format .jpg. Teknik meningkatkan kualitas dan kapasitas gambar digital dilakukan dengan menambahkan dan meningkatkan bit piksel menggunakan metode interpolasi Cubik B-Spline. Cover image yang telah di interpolasi, kemudian disisipi pesan menggunakan metode least significant bit (LSB) untuk memperoleh stegoimage. Pesan yang diselipkan berbentuk file .doc, .docx, .pdf, .xls, .rar, .iso dan .zip dengan ukuran berbeda-beda kapasitasnya. Teknik uji dibuat dengan bantuan perangkat lunak MATLAB versi 2017a. Penelitian melakukan uji dengan mengukur nilai kualitas penyamaran dari stegoimage menggunakan Peak Signal to Noise Ratio (PSNR) dengan rata-rata perolehan stegoimage terhadap Original image 29.06 dB dan stegoimage terhadap Image interpolation 64.34 dB dan uji mean squared error (MSE) dengan rata-rata perolehan 97.54 dB pada Image interpolation terhadap original image dan 97.55 dB pada stegoimage terhadap original image, 0.13 dB nilai MSE stegoimage terhadap Image interpolation. Hasil uji pada penelitian dengan proses interpolasi pada coverimage dengan Cubic B-Spline mempengaruhi terhadap nilai samar atau Nilai PSNR.

Particle geometric is a key parameter that defines the eometric attributes of calcareous sand particles and is intricately related to their mechanical traits, such as compression and shear. The scanning electron microscopy and digital imaging were applied to capture the microscopic properties and geometric projections of calcareous sand. The qualitative analysis, conventional statistical methods and fractal theory were employed to describe the geometric morphology of sand particles. Additionally, we analyzed the structural and physical traits of calcareous sand based on its unique biological genesis. We developed a hypothetical structural-physical model for calcareous sand. Our findings revealed the interwoven reticulation on the surface of calcareous gravel particles, along with an uneven distribution of pores on the external surface. As the particle size increased, the global profile factor decreased and the angularity increased. The critical threshold for the variations in flatness, surface roughness, and circularity was observed at a particle size of 5 mm, with the particle size having a relatively minor effect on these characteristics for particles smaller than 5 mm. The shape of the calcareous sand particles exhibited fractal characteristics, with fractal dimension serving as a measure of surface smoothness, particle breakage, and strength. These experimental results could significantly enhance our understanding of the mechanical behavior of calcareous sand., (© 2024. The Author(s).)

Background: Coffee roasting is one of the crucial steps in obtaining a high-quality product as it forms the product's color and flavor characteristics. Roast control is made by visual inspection or traditional instruments such as the Agtron spectrophotometer, which can have high implementation costs. Therefore, the present study evaluated colorimetric approaches (a bench colorimeter, smartphone digital images, and a colorimetric sensor) to predict the Agtron roasting degrees of whole and ground coffee. Two calibration approaches were assessed, that is, multiple linear regression and least-squares support vector machine. For that, 70 samples of whole and ground roasted coffees comprising the Agtron roasting range were prepared., Results: The results showed that all three colorimetric acquisition types were efficient for the model building, but the bench colorimeter and the smartphone digital images generally performed with good determination coefficients and low errors as measured by external validation. For the whole bean coffee, the best model presented a determination coefficient (R 2 ) of 0.99 and a root-mean-squared error (RMSE) of 1.91%, while R 2 of 0.99 and RMSE of 0.87% was obtained for ground coffee, both using the colorimeter., Conclusion: The obtained models presented good prediction capability, as assessed by external validation and randomization tests. The obtained findings point to an alternative for coffee roasting monitoring that can lead to higher digitalization and local control of the process, even for smaller producers, due to its lower costs. © 2024 Society of Chemical Industry., (© 2024 Society of Chemical Industry.)

The sensorial perception of what is captured is what we know as "image" and consists of a static component and a dynamic process. This continuous process of images capture is essential in surgery. The image is crucial for the surgeon, who requires it for the diagnosis, for the therapeutic process and for postoperative follow-up. In minimally invasive surgery the sequence of images is essential and promotes the appearance of digital video. Digital video is the representation of moving images in the form of encoded digital data, unlike classic analog video, with continuous analog signals. Beyond what we can consider the "real image" (what we see as part of the existing reality) other realities appear in these decades; the Virtual Reality and Augmented Reality. With these realities we refer in the medical ambitus to the creation or superposition, respectively, of a three-dimensional virtual environment to support healthcare and teaching or research processes. Today, these technologies have already begun to be integrated into various surgical specialties, with predictive surgical planning and intraoperative navigation us their main applications. When using these digital environments, it is difficult to completely separate virtual reality from augmented reality, often being Mixed Reality. The current developments offer an environment that mixes the best aspects of both, unifying the simulation and requiring a single helmet or glasses to enjoy the sensorial experience. In this fusion of realities it will be possible to simultaneously create a virtual world from scratch to which we can add virtual elements from our real environment., (Copyright © 2024. Published by Elsevier España, S.L.U.)

In the petroleum and coal industries, digital image technology and acoustic emission technology are employed to study rock properties, but both exhibit flaws during data processing. Digital image technology is vulnerable to interference from fractures and scaling, leading to potential loss of image data; while acoustic emission technology is not hindered by these issues, noise from rock destruction can interfere with the electrical signals, causing errors. The monitoring errors of these techniques can undermine the effectiveness of rock damage analysis. To address this issue, this paper focuses on the restoration of image data acquired through digital image technology, leveraging deep learning techniques, and using soft and hard rocks made of similar materials as research subjects, an improved Incremental Transformer image algorithm is employed to repair distorted or missing strain nephograms during uniaxial compression experiments. The concrete implementation entails using a comprehensive training set of strain nephograms derived from digital image technology, fabricating masks for absent image segments, and predicting strain nephograms with full strain detail. Additionally, we adopt deep separable convolutional networks to optimize the algorithm's operational efficiency. Based on this, the analysis of rock damage is conducted using the repaired strain nephograms, achieving a closer correlation with the actual physical processes of rock damage compared to conventional digital image technology and acoustic emission techniques. The improved incremental Transformer algorithm presented in this paper will contribute to enhancing the efficiency of digital image technology in the realm of rock damage, saving time and money, and offering an innovative approach to traditional rock damage analysis., (© 2024. The Author(s).)

This research presents a novel method for measuring ethanol concentrations using a smartphone. The method involves an oxidation reaction with potassium dichromate and concentrated sulfuric acid, resulting in a green-blue color formation. The color intensity, corresponding to ethanol concentrations ranging from 0 to 100%, was captured using a smartphone camera within a specialized photography box. The images were then analyzed using a specific application, converting the color signal into an absorbance value. The calibration curve demonstrated excellent linearity in the range of 0-0.55 v/v % and its detection limit is 0.01 v/v%, with a correlation coefficient exceeding 0.995. The method was successfully applied to measure ethanol in real samples, including ordinary rose water and a bitter wheat drink.•The method is inexpensive.•The method is rapid.•The method is green., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

Purpose: To compare the applicability of modified US Public Health Service (USPHS) and FDI criteria for evaluating glass ionomer cement (GIC) restorations in primary posterior teeth through digital image analysis., Methods: This comparative analytic study was conducted at the Children's Dental Clinic RSKGM FKG UI, involving 40 GIC restorations on lower first primary molars in children aged 4-9 years. After cleaning, the restorations were assessed clinically using modified USPHS and FDI criteria before taking digital images, then the collected images were re-evaluated using both sets of criteria, and the clinical assessment results were compared to the digital image assessment results., Results: Statistical analysis revealed significant differences between the clinical evaluation of GIC restorations in primary teeth and their corresponding digital photographs when using the modified USPHS criteria, and although the use of FDI criteria yielded different results, these differences were not statistically significant., Conclusion: The assessment of GIC restorations through digital images aligns more closely with clinical assessments using the FDI criteria compared to the modified USPHS criteria., (© 2024. The Author(s), under exclusive licence to European Academy of Paediatric Dentistry.)

This study aims to design and develop learning media in the production orale avancée course using digital images based on local wisdom in Medan in accordance with the demands of DELF level B1 French speaking competence. On the other hand, this study also aims to determine student learning outcomes using digital image learning media in the production orale avancée course. The research method used is the research and development (R & D) with the development procedure of Thiagarajan by carrying out four stages, namely collecting information and data, planning, developing learning media, expert validation of the media and material included. After the four stages were carried out and declared feasible by the validator, the learning media was tested on students in the classroom. The results of material validation in the first stage are 92.30% and 100% in the second validation stage. While the results of the media validation are in the first stage, namely 90.9% and 100% in the second stage. The sample used is 30 students from the fifth semester. [ABSTRACT FROM AUTHOR]

In research from the 1990s, very young children failed to use pictures as representations of real events. Today, many children in the "selfie generation" are constantly photographed by their families using smartphones. While family photos are created, children are exposed to live video on the phone screen that, with a screen touch, becomes an instant photo. Children also revisit these family photos in the phone's photo library. This study explored whether toddlers growing up around smartphone photography are more successful in applying information from a photo to a real event, compared to children in the earlier research. Sixty 2‐year‐old children (23.0–26.2 months; M = 24.5 months) were asked to use pictures of a toy's hiding place (printed photographs or digital photos on an iPhone) to search for the hidden toy in five conditions. Toddlers were not successful with printed or digital images, whether the digital photos were accessed from the phone photo library or the researcher took the photos during the study. However, after children collaborated with the researcher to create digital photos to help an adult confederate, they were significantly more likely to use photos themselves to solve the search task. Children who experienced this scaffolding with printed photos were somewhat more successful than those without training. As with traditional symbolic media, young children's learning from emerging technologies needs the support of an adult who coviews the medium and helps clarify the symbolic relation between screen and world. [ABSTRACT FROM AUTHOR]

Aim: To evaluate the effects of exposure parameters (tube current and voltage) to detect clear and unclear mandibular canals (MCs) using a complementary metal-oxide semiconductor (CMOS) or photo-stimulable phosphor plate (PSP) sensors.Methods: A total of 24 dry half-mandibles were divided into two groups with clear (n = 16) and unclear (n = 8) MCs. The retro-alveolar parallel technique was performed in the six-molar region of the mandibles using direct and indirect digital intra-oral sensors. Six combinations of tube voltage (kV) (60 kV, 66 kV, and 70 kV) and tube current (mA) (2 mA, 5 mA, and 8 mA) were applied, and 144 images of each group were obtained with each CMOS and PSP sensor. Images were processed using Image J software. To evaluate diagnostic accuracy, two square images of the first-molar region were obtained from each image, one with the MC inside and the other without the MC (a total of 576 images were observed). Three radiologists diagnosed the presence or absence of MCs. The diagnostic accuracy of each exposure parameter was compared with the area under the curve (Az) in receiver-operating characteristic analysis.Results: The Az values for clear MCs were higher than those for unclear MCs (P < 0.001). There were no significant differences when the tube current was modified. For unclear MCs, the Az increased when higher tube voltages were used, showing a significant difference using the PSP sensor (p = 0.004). There was no significant difference for clear MCs.Conclusions: Lower exposure parameters should be used for clear MCs, while higher tube voltage values should be used for unclear MCs. [ABSTRACT FROM AUTHOR]

Securing information became essential to exchange multimedia information safely. These exchanged data need to be transformed in a well-managed, secure, and reliable manner. This paper focuses on securing multimedia images via cryptography during transmission among users using an effective selection from several Pseudorandom Number Generators (PRNG). This paper implements several PRNG techniques involved within consecutive cryptoprocesses of substitution and transposition that have proven a secure process. In the study, different PRNGs are tested to encrypt images in forms of grayscale and colored RGB images compared to current similar approaches. The work experimentation is aiming at investigating and identifying suitability and reliability through security measures standard parameters. The research is showing proper PRNG selection as an attractive, significant work worth remarking for image cryptography. [ABSTRACT FROM AUTHOR]

We examine the relationship between convexity and the approxi- mate fixed point property (AFPP) for digital images in Z. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. 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.)

The inherently visual nature of dermatology naturally lends itself to photography. As technology has evolved, smartphone cameras have become ubiquitous and have the potential to improve education and patient care in dermatology. Although patients and physicians may agree that photography can improve patient care, there are certain risks involved with smartphone photography in the medical field. Perhaps most concerning is the number of dermatologists using smartphones to take unsecured images in their daily practice. A recent study revealed that 22% of surveyed dermatologists used smartphone cameras multiple times per day in their practice. Dermatologists may also overestimate patient comfort with smartphone use in clinical photography. We present a review of the use of smartphones in dermatology and address the potential lack of security and accompanying ethical dilemmas.Keywords: Smartphone, iPhone, digital

In recent years, we have seen a significant increase in traffic moving across various networks and channels. The development of technology and global network leads to an increase in the amount of multimedia traffic. To authenticate and avoid abuse, data should be protected with watermarks. This paper discusses various robust and invisible watermarking methods in the spatial domain and the transform domain. The basic concepts of digital watermarks, important characteristics and areas of application of watermarks are considered in detail. The paper also presents the most important criteria for assessing the digital watermark effectiveness. Based on the analysis of the current state of the digital watermarking methods, robustness, imperceptibility, security and payload have been determined as the main factors in most scientific works. Moreover, researchers use different methods to improve / balance these factors to create an effective watermarking system. Our research identified the main factors and new techniques used in modern research. And the assessment of watermark method effectiveness was proposed.

The development of automated systems for detecting defects in and damage to buildings is ongoing in the construction industry. Remaining aware of the surface conditions of buildings and making timely decisions regarding maintenance are crucial. In recent years, machine learning has emerged as a key technique in image classification methods. It can quickly handle large amounts of symmetry and asymmetry in images. In this study, three supervised machine learning models were trained and tested on images of efflorescence, and the performance of the models was compared. The results indicated that the support vector machine (SVM) model achieved the highest accuracy in classifying efflorescence (90.2%). The accuracy rates of the maximum likelihood (ML) and random forest (RF) models were 89.8% and 87.0%, respectively. This study examined the influence of different light sources and illumination intensity on classification models. The results indicated that light source conditions cause errors in image detection, and the machine learning field must prioritize resolving this problem.

As a common preventive maintenance technique for asphalt pavement, micro-surface (MS) has the advantages of waterproofing and crack sealing. However, issues such as the fact that the conventional MS generates large noise and the evaluation of the indexes of tire-road noise are relatively less studied. The traditional surface texture index cannot reveal the range and distribution of pavement surface texture, thus hindering research of low-noise MS. To study the mechanism of tire-road noise generated by MS, and propose the tire-road noise and surface texture indicators for MS. In this study, the mechanism of five low-noise MS was systematically analyzed and compared through surface texture and noise tests. Then, a three-dimensional digital texture model (3D-DTM) of MS surface texture was constructed using a series of digital image processing techniques, including grayscale identification, binary conversion, and noise reduction. The results show that optimizing the gradation, adding sound-absorbing materials, and improving the workability of construction can improve the noise reduction performance of MS, it is worth mentioning that the MS prepared with sound-absorbing materials and low-noise gradation has the greatest noise reduction effect, with a maximum reduction of 6.3 dB(A). In addition, it was also found that the 3D-DTM can well reflect the surface texture characteristics of MS. The probability of convex peak distribution (PCD) and the proportion of convex peak area (PCA) with peak heights greater than 0.25 mm (Kh ≥ 0.25), which are extracted from the 3D-DTM, can well reflect the surface texture, tire-road noise, respectively. The results show that the 3D-DTM is a promising tool to optimize the design of low-noise MS.

Digital image quality measurement is a significant part in image processing systems, especially for efficient transmission. In image compression, the blocking effect is generated due to co-efficient quantification which causes poor quality on the decompressed image. The learning smooth pattern transformation with Greedy method suggests high accuracy in the approximation and classification of data but transformation-invariant coding and classification of digital images were not achieved. Residual component analysis using a Bayesian algorithm estimates the parameters involved to yield a confidence interval but nonlinearity detection was not sensed effectively. In order to overcome the transformation-invariant classification defects and nonlinearity detection, a hybrid approach is introduced in digital images. The hybrid approach is a non-linear discriminate classifier for digital image quality enhancement (NDC-DQE). The NDC-DQE uses class information and finds a set of projection vectors on digital images thereby minimizing the computational complexity. Initially, NDC identifies the degradation type contained in a digital image then measure the quality of that image by using image quality measure for that specific degradation. The NDC-DQE is applied to focus on particular artifacts such as blocking effects and non-blocking effects. The NDC-DQE also uses the statistical framework that covers a large set of common degradations. The NDC-DQE with information fidelity criterion is integrated to derive the mutual information for one subband and multiple subbands. Based on, NDC covers a very large set of possible degradations usually determined in practical digital image used applications. Simulations conducted with NDC-DQE show the performance improvement in image quality in classification accuracy, peak signal to noise ratio, computational complexity, and image quality rate. [ABSTRACT FROM AUTHOR]

Securing information became essential to exchange multimedia information safely. The exchanged data need to be transformed in a well-managed, secure, and reliable manner. In this paper, we will focus on securing RGB images via cryptography during transmission among users using our effective proposal of utilizing appropriate Pseudo Random Number Generator (PRNG). We implement many techniques of PRNG involved in two consecutive crypto-processes of substitution and transposition to present secure image transformation. Our technique proposal of PRNGs selection is based on testing to encrypt RGB images to be compared with current related used approaches. The work experimentation aims to identify suitability and reliability through security measures standard parameters. The research justifies its proper PRNG selection to model our approach as attractive effective work worth remarking. [ABSTRACT FROM AUTHOR]

Video analysis is a very important tool in video surveillance systems with one or more cameras. Among the most promising features are tracking the movement of objects - tracking. The current state of development in the field of tracking is considered in the work. There are several types of trekking. Pixel Tracking is the tracking of the movement of a specific point (pixel) or group of points on the original video sequence. The result of this process is the trajectory of the pixel, corresponding to the movement of an object in the frame. Matchmoving is a complex process that allows you to create a three-dimensional scene with a digital camera based on the available video sequence, which exactly repeats the movement of a real camera. Motion Capture is a technology designed to determine the position and orientation of a real object in a virtual environment, determining the position and orientation of a real object in space is carried out using special sensors and markers. Each of these types of tracking can be used on its own or as part of more complex processes. The paper develops a modification of the camera motion detection algorithm, which works in the field of Pixel Tracking. The description of the main approaches to motion estimation is given, namely recursive raster algorithms, frequency domain algorithms, optical flow algorithms and block matching methods. The urgency of the work, its purpose and objectives are given. The paper describes a method of arranging blocks in a video sequence frame, which are used to calculate the movement of the camera. Similarity metrics are used to estimate the similarity of the blocks, namely the correlation coefficient. The paper describes the steps of the developed modification of the camera motion detection algorithm. The results of the modification of the camera motion detection algorithm are presented. The result of this work is an indicator of the visual quality of tracking in the form of a 2D image of the camera motion vector. [ABSTRACT FROM AUTHOR]

With the development of information technology, the requirements for steganography systems are growing. Today, the steganography system must resist steganalysis attacks using the latest mathematical bases, attacks and countermeasures, which can be easily and efficiently implemented in any modern software environment, providing significant bandwidth when organizing a secret communication channel, and so on. All possible means must be used to meet these requirements. One of the ways to meet a certain requirement is to choose the cover as which the digital image is considered in the study. The cover deciding is to be done in order to provide the best characteristics of stego-object in a sense. The aim of the study is to provide the possibility to choose a cover image, which results in the stego-object that is robust to various image processing attacks. The following results are obtained in the study: the expediency of using perturbations of eigenvectors of the cover image matrix as indicators of security of secret message embedded into the cover is theoretically substantiated and practically confirmed; the quantitative estimation of the perturbation of the eigenvector matrix of the digital image as a result of embedding is proposed, which allows separating the sensitive eigenvector from the insensitive one, adequately reflects the perturbation of the eigenvector regardless of the angle of rotation; the proposed condition for the selection of eigenvectors protected from influence, taking into account the individual characteristics of the cover image; the formula for calculating the amount of protected additional information is proposed; a cover image selection method from the available set of potential containers is developed, which provides stego-object robustness to various image processing attacks. [ABSTRACT FROM AUTHOR]

In the current conditions of constant development of computer technology and networking, the issue of protection of information from unauthorized access is becoming more acute. One of the most effective tools for solving this problem is steganography. The use of steganographic methods allows the transfer of additional information embedded into the container without attracting the attention of outside observers. As a container, it is advisable to use common formats, such as JPEG images, millions of which are circulating on the network every day. There are quite a few steganographic algorithms for JPEG containers, but every year developed new methods of steganalysis that effectively counteract them. Therefore, the improvement of existing and development of new steganographic algorithms remains an urgent task. The aim of this work is to develop a method of embedding additional information in the image using generative adversarial networks for adaptive modification of the container in order to increase resistance to statistical steganalysis. Pre-tuning the container will preserve the distribution of the number of pairs of discrete cosine transform coefficients with certain values. The modern methods of steganalysis are analyzed and the statistical classifier for steganographic algorithm F5 is constructed, the generative adversarial network for preliminary modification of the imagecontainer is developed, efficiency of work of the developed statistical classifier without and with modification of the container is investigated. The results of the experiments showed that the container modified by the generative-competitive network is 36% more resistant to the detection of additional information using the statistical classifier. [ABSTRACT FROM AUTHOR]

The agricultural land mass is more than just being a feeding sourcing in today's world. Agriculture productivity defines the economy of India in a great manner. So, in plants, disease detection plays a vital role in agriculture field. Automatic disease detection approaches are used for detecting plant diseases during the initial stages. To identify the agricultural diseases using digital image based on various features like color, textures and shape. Research firm currently doing a research to detect and diagnosis agricultural diseases based on digital image. This survey provides a better understanding of the soft computing techniques and image processing used for researcher and farmers to identify the agricultural diseases. This survey highlights several diseases of agricultural plants like rice, apple, cucumber, graphs, banana, cherry, wheat and sugarcane. And also this analysis work provides the comparison analysis of different research techniques in terms of their merits and demerits along with numerical analysis. [ABSTRACT FROM AUTHOR]

The aim of this study is to develop a method for detecting the characteristic points in a digital image that is stable under a certain class of brightness transformations. The need for such a method is due to the need to identify key points of images in video surveillance and face recognition systems, which often work in conditions of variations in illumination. A feature of the proposed method, which distinguishes it from a number of well-known approaches to the problem of identifying characteristic points, is the use of the so-called reduced sign representation of images. In contrast to the usual representation of a digital image by its discrete function of brightness, it represents the image by a directed acyclic graph corresponding to the binary relation of increasing brightness over the set of pixels. Thus, the sign representation defines a set of images, the brightness functions of which are connected by strictly monotonic transformations. It is this property of the sign representation that makes it efficient for achievement the aim mentioned above. The next feature of the method under consideration is its approach to the interpretation of the characteristic points of the image. Note that in the modern theory of image processing this concept is not rigorously defined; we can say that the characteristic point is distinguished by the increased complexity of the structure of the image in its vicinity. Since the sign representation of an image is a digraph, in this work the complexity of the structure of paths entering or leaving the given vertex serves as a measure of the complexity of the local neighborhood of its vertex. To carry out experimental studies of the proposed approach, a set of programs was developed, the results of which confirm the efficiency of the method and demonstrate that it is possible to obtain results close to the expected ones using the model examples. The work also offers a number of recommendations for the application of this method. [ABSTRACT FROM AUTHOR]

This article proposes a new end-to-end deep super-resolution crack network (SrcNet) for improving computer vision–based automated crack detectability. The digital images acquired from large-scale civil infrastructures for crack detection using unmanned robots often suffer from motion blur and lack of pixel resolution, which may degrade the corresponding crack detectability. The proposed SrcNet is able to significantly enhance the crack detectability by augmenting the pixel resolution of the raw digital image through deep learning. SrcNet basically consists of two phases: phase I—deep learning–based super resolution (SR) image generation and phase II—deep learning–based automated crack detection. Once the raw digital images are obtained from a target bridge surface, phase I of SrcNet generates the corresponding SR images to the raw digital images. Then, phase II automatically detects cracks from the generated SR images, making it possible to remarkably improve the crack detectability. SrcNet is experimentally validated using the digital images obtained using a climbing robot and an unmanned aerial vehicle from in situ concrete bridges located in South Korea. The validation test results reveal that the proposed SrcNet shows 24% better crack detectability compared to the crack detection results using the raw digital images. [ABSTRACT FROM AUTHOR]

Copyright of Doxa Comunicación is the property of Fundacion Universitaria San Pablo - CEU 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.)

Copyright of Arte, Individuo y Sociedad is the property of Universidad Complutense de Madrid 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.)

In this paper, we have established some new results by extending some existing theorems in the setting of Digital Metric Space. We also proved some results in Digital Metric Space which were established earlier in the context of Complete Metric Space by different authors. [ABSTRACT FROM AUTHOR]

This work aims to analyze the use of images in the scientific dissemination specifically in digital environments, seeking to understand what scientific dissemination is, to follow an approach on the role of image in this type of discourse. For such an undertaking, we take as theoretical basis the notions postulated in the framework of the digital discourse analysis, as proposed by Marie-Anne Paveau (2017), and the discourse of scientific dissemination on the media, by Patrick Charaudeau (2009). Specifically, it aims to (i) reflect on the growing integration of objects connected to our existence, focusing on the functioning of scientific dissemination - and the images it mobilizes - in a digital environment, as well as to (ii) comment on the uses of the image of scientific dissemination in the dialogue with social networks. To do so, images are examined according to the technodiscursive proposals and the iconization category, as well as from the discursive restrictions in the scope of scientific dissemination. The analyses show that, in the sphere of scientific dissemination, the phenomenon of discourse iconization is widely mobilized, both by a scientific dissemination magazine and by the digital enunciators who appropriate it, promoting uses that were not initially foreseen. [ABSTRACT FROM AUTHOR]

Nowadays, neural networks are actively used for data hiding; however, there is currently no systematic knowledge regarding their utilization in this field. This is a significant gap, considering that neural network-based data hiding has already formed a large and quite independent area of research. This review aims to provide such systematization. It also provides a general framework of neural network usage for data hiding, comparisons of quantitative and qualitative indicators of the effectiveness of existing data hiding methods, and discussion and conclusions containing the most promising directions and tools for research in the field of data hiding using neural networks, as well as the main achievements and the persisting challenges. This work targets researchers looking for the most suitable data hiding method for their application, as well as the developers of data hiding methods. [ABSTRACT FROM AUTHOR]

In this paper, a new analytical approach based on smartphone digital-images analysis coupled to chemometrics is proposed to investigate the nature of different pigments of historical and cultural interest. To that end, wall painting replicas were prepared and painted with 9 different pigments covering three colors: yellow, blue, and green. The mockups were photographed with a smartphone, and the images calibrated using a reference color chart. Two approaches were tested: one based on commercial color charts, and other based on lab-made ad hoc charts. The former demonstrated to yield better results, and the calibrated CIELAB coordinates were used to build Support Vector Machines (SVM) as a classification method. The optimized SVMs were able to successfully classify each pigment based on corrected CIELAB color descriptors, with errors of prediction below 5 %. Overall, this paper proposes a fast and non-invasive analytical method based on image treatment and chemometrics to discriminate among historical pigments in wall painting replicas. • A novel smartphone image-based method is presented to study historical pigments. • Different training sets for colorimetric characterization are compared. • Three painting techniques are applied and their effect on color assessed. • Successful pigment identification is obtained using Support Vector Machines (SVM). • An image-based protocol to correctly evaluate historical pigments' color is shown. [ABSTRACT FROM AUTHOR]

The article presents a brief analysis of the existing methods of internal target designation used on existing models of armored weapons. The authors propose the method of internal target designation and target indication based on the mathematical description of interrelation between coordinates of the image of an object in the visual field of a sight and its three-dimensional coordinates in world coordinate system.

The digital society has transformed our cognitive, social, productive and aesthetic experience of the world. Many deep and continuous changes, still in progress and harbingers of the next adjustments, will occur due to the imminent evolution of digital technologies into environmental holistic infosphere, where it seems to delineate the integration between virtual and physical. The focus is on some changes of the Representation’s scientific discipline and interrogations on the future scenarios: the following reflections deal with the impact of digital on architecture and representation and how much the mediascape has influenced the current digital processes of production, reproduction and distribution of images modifying our perception and experience of space, time, material, senses and identity.

This paper tackles with two methods to dimensionality reduction, namely principal component analysis (PCA ) in the case of linear combinations and kernel principal component analysis method in the case of nonlinear combinations to digital image processing and analysis for useful information .And then compare the two methods and know which methods are appropriate to imaging dimensionality reduction The methods were applied to a group of satellite images of an area in the province of Basra, which represents the mouth of the Tigris and Euphrates in the Shatt al-Arab, as well as the water channels permeating Basra Governorate and the water bodies scattered around these channels.In this research, it is shown that the fourth image band is best when using the PCA method the value of it is eigen value was the biggest ,while the KPCA method showed that the third image band was the best, giving the highest latent value. Comparing the two methods using the mean error error (MSE) method, the results showed that the main KPCA method was the best.

The presence of discontinuities and randomly distributed pores in basalt specimens greatly affects their engineering properties, such as the failure mechanism and strength. Therefore, investigating the mechanical and fracture behaviors of basalt affected by the pre-existing defects is important for underground engineering, mining engineering, foundation engineering, and rock breaking and blasting. Laboratory tests have been widely used to research the failure mechanism of rocks under different conditions. However, it is difficult to clearly show the internal or spatial crack evolution during rock failure process in laboratory tests. Recently, X-ray computerized tomography (CT) and numerical tests have been used to detect the internal microstructures of rock specimens and to study their failure mechanism and strength. In addition, tensile strength is an important mechanical property of rock material. The direct tensile test is theoretically the simplest and most effective method for understanding the tensile behavior of rock. However, it is difficult to carry out in practical condition, because the sample processing and test procedures are complicated, also the experimental process of each sample cannot be repeated and has limited results. Due to the opacity of rocks, it is difficult to examine the three-dimensional internal structures of rocks through traditional physical and numerical experiments. In the present research, a 3D numerical method was proposed for simulating porous rock failure based on CT technology, the edge detection algorithm, filtering algorithm, and 3D matrix mapping method. Direct tensile tests were carried out based on the parallel finite element method to study the effect of the porosity and pore distribution on the failure mechanism and tensile strength. The results indicate that initial cracks at the beginning of loading usually occur in pores, and then with the raising of load the initial cracks propagate along the direction perpendicular to the loading direction and eventually form macroscopic tensile cracks. The porosity and pore distribution have significant influences on the position of macroscopic tensile cracks. The acoustic emission (AE) event numbers and the accumulative AE energy are gradually decreased as the porosity increased. In addition, the brittle failure primarily determines the tensile failure mode and the presence of pores weakens the tensile strength of basalt samples.

An artist would have at his or her disposal a plethora of calligraphy units to produce his works integrating visual units that are eye catching to connoisseur fans.Arabic calligraphy closely relates to artistic, and cultural advancements that go hand in hand. Undoubtedly, calligraphy art and writing activity in general constitute an important part of a living cultural heritage at its best. Arabic Language remains a corner stone of Islamic civilization.It has been a flexible , comprehensive, and dignified vehicle for Arabs to express their thoughts and inner feelings throbbing with their distinctive cultural identity.Needless to say, writing and language distinguish us human beings from other creation,and thus they are distinctive characterizations of human civilization as a whole. As part of wide spread technological advancements, many artists have been seeking to formulate Arabic script using computer software added to digital images to produce graphic design and plastic art as well due to the desired speed to accomplish such tasks.The researcher embarked on digital experimentation by integrating Arabic letters with digital images she created to produce a series of digital graphic design work.The problem of the research materializes in the question of how far digital technology would create graphics and plastic design artwork through the process experimentation leading to innovative design units that would attain equal standing with work purely produced by hand in the traditional way.Objectives of the Research1. To define the artistic mechanisms of Arabic calligraphy dynamics of formulation to produce graphic design works.2. To pinpoint the potential of digital imaging: the what and how of digital works of art.3. To produce innovative graphic design experiments that express visually the individualistic character of the researcher as an artist through integrating Arabic calligraphy script with digital images Limits of Current Research Project1. Arabic Letters2. Digital Images Hypothesis of the Research1. To produce digital graphic design works characterized by an innovative visual perspective through formulating Arabic script at a back drop of digital imaging techniques.Axes of the Research Project The current research includes :1. Former studies2. Arabic script and digital imaging3. Experiments by the researcher4. Analysis of resultsKeywords1. Arabic letters2. Digital imaging3. Graphic Design Production