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The nuclear industry and other high-radiation environments often need remote monitoring equipment with advanced cameras to achieve precise remote control operations. CMOS image sensors, as a critical component of these cameras, get exposed to γ-ray irradiation while operating in such environments, which causes performance degradation that adversely affects camera resolution. This study conducted total ionizing dose experiments on CMOS image sensors and camera systems and thoroughly analyzed the impact mechanisms of the dark current, Full Well Capacity, and quantum efficiency of CMOS image sensors on camera resolution. A quantitative evaluation formula was established to evaluate the impact of Full Well Capacity and quantum efficiency of the CMOS image sensor on camera resolution. This study provides a theoretical basis for the evaluation of the radiation resistance of cameras in environments with strong nuclear radiation and the development of radiation-resistant cameras. [ABSTRACT FROM AUTHOR]

The replacement of rear-view mirrors with camera-monitor systems introduces new opportunities for design, such as altering the image quality and the rearward field-of-view. We investigated how the image quality and field-of-view might affect the distance and time-to-contact estimation of other vehicles. Eighty-six subjects estimated either their egocentric distance to a stationary vehicle (Experiment I) or the time-to-contact to an approaching vehicle (Experiment II). Throughout the experiments, the pixel density and either the field-of-view or the viewing condition varied. A larger field-of-view increased distance estimation accuracy and confidence. Reduced pixel density led to larger estimates. In contrast, reduced pixel density and simulated dirt shortened time-to-contact estimates. This is compatible with a safety strategy applied under conditions of impaired vision. Moreover, a limited benefit was observed for higher pixel densities. Therefore, camera-monitor systems with large field-of-view and a pixel density of around 300 ppi could ensure accurate TTC and distance estimation. Practitioner summary: A camera's field-of-view and image quality are important parameters for camera-monitor systems. In two experiments, we investigated the effects of these two parameters on rearward distance and time-to-contact estimation. Whereas a larger field-of-view improved distance estimation accuracy, increasing the pixel density had a limited effect in the estimation of time-to-contact. [ABSTRACT FROM AUTHOR]

Taxicab security cameras are widely used to deter crimes against taxicab drivers in two-row-seating taxicabs. Some of these cameras have difficulty for use in three-row-seating taxicabs due to increased distance between the camera and the third-row seats. This project tested five sample taxicab security cameras with different image-sensor pixel counts to determine their utility for three-row-seating taxicabs. The cameras videotaped a normalized camera resolution test chart mounted in the third-row seat of a simulated three-row-seating taxicab in both daylight and dark (with infrared radiation) conditions. The resolution of each camera was measured and compared with the resolution threshold for customer facial identification. A dome-mounted camera with a standard-definition image-sensor is suggested as an effective camera in sustaining high camera resolution with small data file size for facial identification in the third-row seats. The image-sensors with at least 1280 × 720 pixels are suggested for windshield-mounted cameras in three-row-seating taxicabs for facial identification. [ABSTRACT FROM AUTHOR]

Imaging sensor development results, achieved in the past four decades, provide increased camera capabilities both in day and night conditions. Due to advanced camera performances, we are experiencing a wide application of the imaging sensors in various areas, e.g. machine vision, mobile technology, autonomous vehicle driving, smart city scenarios, and scientific imaging. Low light level sensitivity, supporting camera night vision capability, leads to new applications in the security systems. Accordingly, the new needs of the camera testing procedures appear. Advanced camera performances also require a new approach to imaging sensor and camera testing and parameter definition. The short review of the current achievements in the area of low light camera technology developments is presented as a basis to illustrate the importance of their application and proper metrological support development. The review of the most important low light camera parameters and related measurement and testing methods is set to point out the needs for new low light camera testing procedures development.

Rice is a staple that is cooked so that it becomes rice for daily consumption. The type of rice that is often used for daily consumption is white rice. There are several types of white rice circulating in the market that are consumed by the public. Each type of rice gives different scent, taste and price. This study compares the accuracy of white rice type recognition based on several camera resolutions. The types of rice used in this study are Jawa Barat rice, Jawa Timur rice, Pandan Wangi rice, Thailand rice and Vietnam rice. The camera resolution used is 5MP, 8 MP, 12 MP, 14 MP, and 16MP. The shooting distance used is ± 9 cm between the camera and the object of rice. The recognition method used is BackPropagation Artificial Neural Networks, while for feature extraction using the Gray Level Co-occurrence Matrix (GLCM) which consists of contrast, energy, homogeneity, and correlation. The highest results obtained at 12 MP camera resolution with the results of the recognition of 25 of 50 test data and the results of the calculation with confusion matrix obtained an average accuracy of 82%, precision of 55%, and recall of 50%. The results of this study can be used as a reference for research that uses objects of similar character, or further research with the same object in developing applications that are ready to use.

Most existing machine vision‐based location methods mainly focus on the spatial positioning schemes using one or two cameras along with non‐vision sensors. To achieve an accurate location, both schemes require processing a large amount of data. In this study, the authors propose a novel method, which requires much less amount of data to be processed for measuring target distance using monocular vision. Based on the geometric model of camera imaging, the parameters of the camera (such as camera's focal length and equivalent focal length.), as well as the principle of analogue signal being transformed into a digital signal, the authors derive the relationship among the target distance, field of view, equivalent focal length and camera resolution. Experimental results show that the proposed method can effectively and accurately achieve the target distance measurement. [ABSTRACT FROM AUTHOR]

The midday stem water potential (Ψs) and stomatal conductance (gs) have been traditionally used to monitor the water status of cherry trees (Prunus avium L.). Due to the complexity of direct measurement, the use of infrared thermography has been proposed as an alternative. This study compares Ψs and gs against crop water stress indexes (CWSI) calculated from thermal infrared (TIR) data from high-resolution (HR) and low-resolution (LR) cameras for two cherry tree cultivars: ‘Regina’ and ‘Sweetheart’. For this purpose, a water stress–recovery cycle experiment was carried out at the post-harvest period in a commercial drip-irrigated cherry tree orchard under three irrigation treatments based on Ψs levels. The water status of trees was measured weekly using Ψs, gs, and compared to CWSIs, computed from both thermal cameras. Results showed that the accuracy in the estimation of CWSIs was not statistically significant when comparing both cameras for the representation of Ψs and gs in both cultivars. The performance of all evaluated physiological indicators presented similar trends for both cultivars, and the averaged differences between CWSI’s from both cameras were 11 ± 0.27%. However, these CWSI’s were not able to detect differences among irrigation treatments as compared to Ψs and gs.

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• A novel method using deep learning-based amplification and tracking is proposed to measure the micro-vibration. • This method can be used under complex light fields with different illumination and backgrounds. • The target object is first magnified and tracked, and then converted into actual displacement values. A new deep learning-based vision measurement method is proposed to accurately measure the micro-vibration displacements of objects in different illuminations and backgrounds. The measurement method pre-process the video, then the deep learning correlation methods are used to zoom in the target object and track the vibration trajectory, and the pixel displacement is converted to actual displacement by pixel equivalents. By comparing the three sets of experiments, the proposed method has exceptional accuracy. When measuring vibration displacement of 0.1 mm, the Root Mean Square Error (RMSE) and Normalized Root Mean Square Error (NRMSE) are 0.0234 mm and 11.8601 %. By comparing with the Rectangle Detection Algorithm and the Template Matching Algorithm, the proposed algorithm outperforms these two traditional methods, especially for the complex environments. It can be concluded that this method, as a new visual measurement method, can be adapted to a variety of complex environments and can accurately measure micro-amplitude vibrations. [ABSTRACT FROM AUTHOR]

An investigation of how increasing the distance and angle to objects of interest affected the measurement accuracy and precision achievable with high-definition and medium-resolutionPAL stereo-video systems was conducted. A test was also conducted to determine whether varying the compression of the imagery influenced measure the accuracy and precision. Measurements of five different lengths of PVC pipe (ranging from 51.5 to 3,001 mm) that represented the lengths of reef fishes routinely sampled with stereo-video were made at 1 m intervals out to the maximum visibility :(9 m range) over threedifferentangles (900, 80° and 70°). High-definition stereo-video imagery was compressed at three different bit-rates. The results show that higher definition stereo-video imagery allows objects to be measured more accurately and precisely over greater ranges, When both ends of a target can be clearly seen in high-definition stereo-video imagery, the associated error is approximately 1% of the total lengft of the object. There was no deleterious effect on accuracy or precision from increasing the angle of view. Lower compression did not result in more accurate and precise length estimates. The configuration of a stereo-video system needs to match the task ofa particular survey, as changes in the base separation and angle of convergence will affectthe accuracy and precision of measurements. With full high-definition systems, smaller lengths (<50 mm) of PVC could not be accurately measured at distances greater than 5 m whereas longer lengths (500-3,001 mm) could be measured with acceptable accuracy and precision at 9 m. [ABSTRACT FROM AUTHOR]

The midday stem water potential (Ψs) and stomatal conductance (gs) have been traditionally used to monitor the water status of cherry trees (Prunus avium L.). Due to the complexity of direct measurement, the use of infrared thermography has been proposed as an alternative. This study compares Ψs and gs against crop water stress indexes (CWSI) calculated from thermal infrared (TIR) data from high-resolution (HR) and low-resolution (LR) cameras for two cherry tree cultivars: 'Regina' and 'Sweetheart'. For this purpose, a water stress–recovery cycle experiment was carried out at the post-harvest period in a commercial drip-irrigated cherry tree orchard under three irrigation treatments based on Ψs levels. The water status of trees was measured weekly using Ψs, gs, and compared to CWSIs, computed from both thermal cameras. Results showed that the accuracy in the estimation of CWSIs was not statistically significant when comparing both cameras for the representation of Ψs and gs in both cultivars. The performance of all evaluated physiological indicators presented similar trends for both cultivars, and the averaged differences between CWSI's from both cameras were 11 ± 0.27%. However, these CWSI's were not able to detect differences among irrigation treatments as compared to Ψs and gs. [ABSTRACT FROM AUTHOR]