Coded aperture snapshot spectral imager (CASSI) has been a popular spectral imaging architecture for its ability of capturing hyperspectral images with high temporal resolution. However, such snapshot imaging system e...
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ISBN:
(纸本)9781538649923
Coded aperture snapshot spectral imager (CASSI) has been a popular spectral imaging architecture for its ability of capturing hyperspectral images with high temporal resolution. However, such snapshot imaging system entails a large sacrifice in the spatial resolution of the data cube, since only a small amount of light gets into the imager during one snapshot. Also, the spatial resolution of the CASSI system is limited by the pixel size (and amount) of the detector, while it is difficult to fabricate a dense detector with small pixel size, especially for infrared spectral bands. Super-resolution is an advanced post-processing technique to alleviate such problem by exploiting the prior information of the image. In this letter, we try to realize image super-resolution from the perspective of developing new form of measurements by taking advantage of a modified CASSI system equipped with a coded aperture with higher spatial resolution than the detector, merging the SR model into the hardware configuration. Then the original data cube can be reconstructed from lower resolution measurements, thus the super-resolution is realized during the compressive sensing reconstruction process. The new system can be achieved based on the classical CASSI architecture in two dual ways, one by replacing the coded aperture with a higher resolution one and the other by substituting the focal plane array (FPA) detector with a lower resolution one. The experiments show that, we can recover images of higher quality with the first modification of CASSI system above, simply using a higher resolution coded aperture.
Edge detection is one of the significant properties of many computervision systems in image recognition, enhancement, compression, restoration, and so on. Though many research results were published, researchers stil...
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ISBN:
(数字)9781728193335
ISBN:
(纸本)9781728193342
Edge detection is one of the significant properties of many computervision systems in image recognition, enhancement, compression, restoration, and so on. Though many research results were published, researchers still try to develop a more efficient edge detection algorithm that meets the current needs. We propose an image pre-processing based edge detection technique using canny edge detector. The main problem of canny edge detector is that it cannot identify the edges which are slightly vague due to the Gaussian smoothing. In this study, we solve the problem using the histogram processing of an image before using the canny edge detector. The result demonstrates that the proposed approach gives better outcomes compared to the state-of-the-art edge detectors.
In recent years, there has been a remarkable increase in interest and challenges in imageprocessing and pattern recognition, specifically in the context of air writing. This exciting research area has significant pot...
In recent years, there has been a remarkable increase in interest and challenges in imageprocessing and pattern recognition, specifically in the context of air writing. This exciting research area has significant potential to advance automation processes and improve human-machine interfaces in various applications. The emergence of faster computers, affordable high-performance video cameras, and the need for automated analysis of videos has led to an increase in the popularity of object tracking, a critical task in computervision. The process of video analysis typically encompasses object detection, tracking, and behavior analysis. Object tracking involves four main aspects choosing the suitable object representation, selecting features for tracking, detecting the object, and tracking the object. Object tracking algorithms find applications in different domains, including vehicle navigation, video indexing, and surveillance that are automated. The objective of the paper is to create a software application for smart wearable devices that utilizes computervision to track finger gestures in the air, functioning as a motion-to-text converter for air-writing. The technology will facilitate communication for people by enabling them to generate text for multiple purposes, like sending emails and messages, through intermittent gestures. This is a productive means of communication that curbs the usage of laptops and mobiles, making it particularly beneficial for individuals who are deaf.
Diabetic retinopathy is an eye disease caused by swelling in blood vessels. If it gets worse the blood vessels will rupture and this is the main factor of blindness. This disease is rarely found in children and sympto...
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This paper presents an innovative framework that employs camera-captured visual data to detect and suggest optimal sitting postures. The framework consists of two crucial components: a video capture object and an obje...
This paper presents an innovative framework that employs camera-captured visual data to detect and suggest optimal sitting postures. The framework consists of two crucial components: a video capture object and an object detection system that incorporates Deep Learning to enhance efficiency and reliability. The camera initially captures the user’s posture image, which is then subjected to video processing to extract video metadata. Subsequently, the object is created by extracting the image from the video, and the object detection algorithm is applied to provide posture recommendations. The algorithm continually monitors posture correctness and provides suggestions to improve it as necessary, ultimately benefiting the user’s daily life and mitigating potential long-term problems. Additionally, the algorithm can be further developed to recognize posture patterns and suggest corrective exercises or techniques. Furthermore, the algorithm’s efficiency can be enhanced by optimizing landmark detection for more effective outcomes. This cutting-edge framework offers immense potential for improving posture and overall health, and its development can significantly enhance the quality of life for individuals.
Machine vision has become a new technique in the AI field of imageprocessing as an important and useful technique. Thus, it is significant to study image fusion on train fault. image fusion mainly studies the image d...
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ISBN:
(数字)9781538671412
ISBN:
(纸本)9781538671429
Machine vision has become a new technique in the AI field of imageprocessing as an important and useful technique. Thus, it is significant to study image fusion on train fault. image fusion mainly studies the image data fusion technology to obtain a synthetic image including the multiple images of the same scene from many different patterns by the image sensors or the same sensor at the different time. In this paper, the images are collected form the bogie and coupler draft devices in the operation of train, and these images are merged based on wavelet transform. Compared with the weighted average fusion method about the fusion results of subjective and objective evaluation the superiority of wavelet transform is fully proved.
Edge is an important features required by many computervision *** crucial step of edge or line detection is *** orientation in a gray scale image provides an important clue for *** this paper,an algorithm,used for ed...
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Edge is an important features required by many computervision *** crucial step of edge or line detection is *** orientation in a gray scale image provides an important clue for *** this paper,an algorithm,used for edge or grouping based on the local orientation information,is proposed. The results are shown,and compared with wellknown transform.
image segmentation plays an important role in imageprocessing and computervision. The pulse coupled neural network has been applied in image segmentation. The pulse coupled neural network model has many parameters w...
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ISBN:
(数字)9781728135847
ISBN:
(纸本)9781728135854
image segmentation plays an important role in imageprocessing and computervision. The pulse coupled neural network has been applied in image segmentation. The pulse coupled neural network model has many parameters which have the influence on the performance. And the parameters optimization becomes a problem. Bat algorithm is inspired by the echolocation behavior of natural bats in determining their foods and also applied in many optimization problem. In this paper, the bat algorithm is used to optimize the parameters of pulse coupled neural network and the pulse coupled neural network is applied in image segmentation. The results show that the new algorithm has better performance than the threshold algorithm and otsu image segmentation algorithm.
When automatic patrol robots trying to identify road boundaries through edge detection, road marking lines on the road may cause errors. In this regard, this paper proposes a method to process images base on edge dete...
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ISBN:
(纸本)9781450376754
When automatic patrol robots trying to identify road boundaries through edge detection, road marking lines on the road may cause errors. In this regard, this paper proposes a method to process images base on edge detection results, and builds a system based on the method for experiments. The experimental results show that the proposed method can effectively reduce the edge features of road markings lines while preserving the edge features of real boundaries, so that robots can identify real road boundaries.
The use of computervision to detect and recognize target objects in the industrial field has high academic value. In this paper, computervision is used to identify cell39;s label and detect the surface scratch. Us...
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ISBN:
(纸本)9783037857106
The use of computervision to detect and recognize target objects in the industrial field has high academic value. In this paper, computervision is used to identify cell's label and detect the surface scratch. Using inter variance threshold method of image acquisition threshold processing, to obtain a better image binarization, subsequent using characterization information to establish a template, and the template using mathematical morphology operations. Object matching is achieved by matrix change of the template, in order to achieve the detection. The experiments show that this method has higher accuracy and better real-time, so online detection can be used for battery characterization.
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