Electrophoretic display (EPD) has become one of the most important display technologies due to its bistability, low power consumption and outdoor readability. In this work, an image processing algorithm, which aims to...
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Electrophoretic display (EPD) has become one of the most important display technologies due to its bistability, low power consumption and outdoor readability. In this work, an image processing algorithm, which aims to enable video playback on EPD device without image distortion and grayscale loss by reducing the particle moving distance in EPD, is proposed and verified. The refresh time could be shortened by 22.2% with a video playback speed of more than 10 frames per second (fps) being achieved. This method could reduce the EPD switching time for quicker information displaying, and potentially extend the applications of EPD with video-like display property in the future.
In the paper, a shift of individual human erythrocytes drifts speed, stimulated by various low-power lasers irradiation, was studied by digital holographic microscopy (DHM). Well known in physiotherapy, a low-levellas...
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In the paper, a shift of individual human erythrocytes drifts speed, stimulated by various low-power lasers irradiation, was studied by digital holographic microscopy (DHM). Well known in physiotherapy, a low-levellaser-therapy (LLLT) scanner was used as the stimulation light source, with diode and He-Ne lasers to compare. In the article, an open-source image processing algorithm for simultaneous dynamics and geometrical properties evaluations of the red blood cells is proposed. A strong influence of the low-level red light on the red blood cells dynamics was observed. The effect is important for a better understanding of the laser treatment mechanism. The proposed phase image analysis algorithm significantly improves the individual cells tracing precision for a life science application. The programme might be useful for optical tweezer, imaging flow cytometry, or high precision cells-photon interaction research.
Optical coded targets allow to determine the relative pose of a camera, on a metric scale, from one image only. Furthermore, they are easily and efficiently detected, opening to a wide range of applications in robotic...
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Optical coded targets allow to determine the relative pose of a camera, on a metric scale, from one image only. Furthermore, they are easily and efficiently detected, opening to a wide range of applications in robotics and computer vision. In this work we describe the effect of pixel saturation and non-ideal lens Point Spread Function, causing the apparent position of the corners and the edges of the target to change as a function of the camera exposure time. This effect, which we call exposure bias, is frequent in over or underexposed images and introduces a systematic error in the estimated camera pose. We propose an algorithm that is able to estimate and correct for the exposure bias exploiting specific geometric features of a common target design based on concentric circles. Through rigorous laboratory experiments carried out in a highly controlled environment, we demonstrate that the proposed algorithm is seven times more precise and three times more accurate in the target distance estimation than the algorithms available in the literature. (c) 2021 Elsevier Ltd. All rights reserved.
An important area in a gathering place is a region attracting the constant attention of people and has evident visual features, such as a flexible stage or an open-air show. Finding such areas can help security superv...
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An important area in a gathering place is a region attracting the constant attention of people and has evident visual features, such as a flexible stage or an open-air show. Finding such areas can help security supervisors locate the abnormal regions automatically. The existing related methods lack an efficient means to find important area candidates from a scene and have failed to judge whether or not a candidate attracts people's attention. To realize the detection of an important area, this study proposes a two-stage method with a novel multi-input attention network (MAN). The first stage, called important area candidate generation, aims to generate candidate important areas with an image-processingalgorithm (i.e., K-means++, image dilation, median filtering, and the RLSA algorithm). The candidate areas can be selected automatically for further analysis. The second stage, called important area candidate classification, aims to detect an important area from candidates with MAN. In particular, MAN is designed as a multi-input network structure, which fuses global and local image features to judge whether or not an area attracts people's attention. To enhance the representation of candidate areas, two modules (i.e., channel attention and spatial attention modules) are proposed on the basis of the attention mechanism. These modules are mainly based on multi-layer perceptron and pooling operation to reconstruct the image feature and provide considerably efficient representation. This study also contributes to a new dataset called gathering place important area detection for testing the proposed two-stage method. Lastly, experimental results show that the proposed method has good performance and can correctly detect an important area.
The movement analysis of the human body is an interesting task for applications in rehabilitation assisted by robots and robotic manipulation. This paper presents a simplified system using the Kinect sensor and simple...
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ISBN:
(纸本)9781457711992
The movement analysis of the human body is an interesting task for applications in rehabilitation assisted by robots and robotic manipulation. This paper presents a simplified system using the Kinect sensor and simple image processing algorithms for the extraction of identification points. Experiments were conducted to identify whether the sensor has good characteristics for the considered applications. A repeatability experiment were carried out and its results indicate that the sensor can be used to measure three-dimensional identification points distances regarding the applications requirements within the operational range from 0.5m up to 2m.
Bionic electronic eye (Bionic e-Eye), a developed smartphone-based colorimetric reader system, consists of smartphone or pad (iPhone 4s or iPad 3) as detection instrument and portable accessory as illumination provide...
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ISBN:
(纸本)9781424492695
Bionic electronic eye (Bionic e-Eye), a developed smartphone-based colorimetric reader system, consists of smartphone or pad (iPhone 4s or iPad 3) as detection instrument and portable accessory as illumination provider, integrating with a wide-angle lens, a piece of lowest-power electro luminescent and a custom-made dark hood. A 96-well microtiter plate (MTP) was positioned on the electro luminescent and Bionic e-Eye captures the detection images by the back camera of smartphone. Being similar to human visual system, the hue, saturation and value (HSV, also called hex cone model) color model was employed in image processing algorithm of Bionic e-Eye. Optimized system dimension was determined by the system steadiness experiment of different photograph distances. Moreover, the commercially available BCA protein assay and CCK8 cell number assay were carried out to evaluate this Bionic e-Eye. Analytical performance of Bionic e-Eye had the better precision, higher sensitivity than microtiter plate reader (MTPR) and previous smartphone-based colorimetric reader for both two assays. Also, Bionic e-Eye using optical image detection had simultaneous and synchronous working mode, while MPTR using machine moving detection had asynchronous working mode in high throughput detection. Therefore, Bionic e-Eye will be an ideal point-of-care (POC) colorimetric detection device in the field of clinical application, industrial quality control, environment monitoring, and food assessment.
In TFT-LCD manufacturing process, various defects are generated by manufacturing machine trouble or particle. These defects can be repaired through the TFT-laser repair process that only canpsilat be automated in TFT-...
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ISBN:
(纸本)9784907764302
In TFT-LCD manufacturing process, various defects are generated by manufacturing machine trouble or particle. These defects can be repaired through the TFT-laser repair process that only canpsilat be automated in TFT-LCD manufacturing process. In this paper, we propose auto defect algorithm for TFT-LCD laser repair machine using image processing algorithm in order to automate process. Proposed algorithm can detect very small defects (under 2 um) in 98% success ratio, and generated laser repair path guarantee highly precise position accuracy. Through proposed system, much of the work still done the old-fashioned way, by hand, can be automated and manufacturing company can be strengthen the competitiveness of cost.
Vascular segmentation through the use of imageprocessing tools provides significant information that allows for the accurate diagnosis, categorization, registration, and visualization of vascular disease. Currently, ...
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ISBN:
(纸本)9781467317139
Vascular segmentation through the use of imageprocessing tools provides significant information that allows for the accurate diagnosis, categorization, registration, and visualization of vascular disease. Currently, in the assessment of Abdominal Aortic Aneurysms (AAA), radiologists manually segment different regions on interest on each medical image to create a full volume of the abdominal aorta. Such manual segmentation is a time consuming task, prone to errors and a subjective approach especially when non-contrast enhanced images are present. In this paper, we introduce an automatic system to segment the aortic lumen in non-contrast enhanced CT scans and PC-MR images using digital image processing algorithms where image enhancement, denoising, edge detection, and regional growing algorithms are utilized. The output of this work forms the basis for a future reliable inner and outer wall segmentation of the AAA.
In order to solve the problem of automation of cable number identification in the process of cable assembly of large equipment, we proposed a cable number detection and recognition method based on image Maximally Stab...
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ISBN:
(纸本)9781728123264
In order to solve the problem of automation of cable number identification in the process of cable assembly of large equipment, we proposed a cable number detection and recognition method based on image Maximally Stable Extremal Regions (MSER) and convolutional neural network (CNN). We used image processing algorithms combined with deep learning to achieve end-to-end identification of cable number images. In view of the uncertain arrangement order and scattered distribution of numbers on the cable, the MSER algorithm was improved by imageprocessing in order to extract the area containing numbers more accurately. The number identification problem in the case of lack of sample database is solved by the migration-trained CNN network. In addition, the recognition effect of the method under different environmental conditions has been studied. Through experimental research, the optimized MSER and CNN algorithms can better complete the cable number detection and identification tasks.
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