An objectifying system for color inspections of traditional Chinese medicine （CITCM） is developed. The entire system includes two parts ： The hardware and the software. The hardware is an image acquiring device und...An objectifying system for color inspections of traditional Chinese medicine （CITCM） is developed. The entire system includes two parts ： The hardware and the software. The hardware is an image acquiring device under a standard lighting condition, and it mainly includes a xenon lamp with color temperature of 5 500 K as light source, an integrating sphere used for diffusing light and a high resolution CCD camera. The software is used for digital image processing, and the procedure is divided into three steps. Firstly the skin/non-skin classifi- cation is performed by utilizing the threshold in chrominance channels of the RGB color space. Secondly, the fa- cial features are localized by using the image segmentation and coordinates sorting. Finally, the facial special re- gion（SR） corresponding to five internal organs is achieved by utilizing masks designed to take advantage of mor- phology. Subsequently, the chromaticity is calculated. The system is tested by taking 83 samples of 30 young and 53 elderly people. The experiment shows that there is significant difference of all SRs between the young and the elderly, and the system has better performance for objectifying research of CITCM.展开更多
This paper presented an online quality inspection system based on artificial neural networks. Chromatism classification and edge detection are two difficult problems in glass steel surface quality inspection. Two arti...This paper presented an online quality inspection system based on artificial neural networks. Chromatism classification and edge detection are two difficult problems in glass steel surface quality inspection. Two artificial neural networks were made and the two problems were solved. The one solved chromatism classification. Hue, saturation and their probability of three colors, whose appearing probabilities were maximum in color histogram, were selected as input parameters, and the number of output node could be adjusted with the change of requirement. The other solved edge detection. In this neutral network, edge detection of gray scale image was able to be tested with trained neural networks for a binary image. It prevent the difficulty that the number of needed training samples was too large if gray scale images were directly regarded as training samples. This system is able to be applied to not only glass steel fault inspection but also other product online quality inspection and classification.展开更多
A new local cost function is proposed in this paper based on the linear relationship assumption between the values of the color components and the intensity component in each local image window,then a new quadratic ob...A new local cost function is proposed in this paper based on the linear relationship assumption between the values of the color components and the intensity component in each local image window,then a new quadratic objective function is derived from it and the globally optimal chrominance values can be computed by solving a sparse linear system of equations.Through the colorization experiments on various test images,it is confirmed that the colorized images obtained by our proposed method have more vivid colors and sharper boundaries than those obtained by the traditional method.The peak signal to noise ratio(PSNR) of the colorized images and the average estimation error of the chrominance values relative to the original images also show that our proposed method gives more precise estimation than the traditional method.展开更多
General active contour algorithm, which uses the intensity of the image, has been used to actively segment objects. Because the objects have a similar intensity but different colors, it is difficult to segment any obj...General active contour algorithm, which uses the intensity of the image, has been used to actively segment objects. Because the objects have a similar intensity but different colors, it is difficult to segment any object from the others, Moreover, this algodthm can only be used in the simple environment since it is very sensitive to noise. In tinter to solve these problems. This paper proposes an extended active contour algorithm based on a color variance. In complex images, the color variance energy as the image energy is introduced into the general active contour algorithm. Experimental results show that the proposed active contour algorithm is very effective in various environments.展开更多
基金Supported by the Innovation Team Fund of Nanjing University of Aeronautics and Astronauticsthe Chinese Medical Association Research Project(S10)~~
文摘An objectifying system for color inspections of traditional Chinese medicine （CITCM） is developed. The entire system includes two parts ： The hardware and the software. The hardware is an image acquiring device under a standard lighting condition, and it mainly includes a xenon lamp with color temperature of 5 500 K as light source, an integrating sphere used for diffusing light and a high resolution CCD camera. The software is used for digital image processing, and the procedure is divided into three steps. Firstly the skin/non-skin classifi- cation is performed by utilizing the threshold in chrominance channels of the RGB color space. Secondly, the fa- cial features are localized by using the image segmentation and coordinates sorting. Finally, the facial special re- gion（SR） corresponding to five internal organs is achieved by utilizing masks designed to take advantage of mor- phology. Subsequently, the chromaticity is calculated. The system is tested by taking 83 samples of 30 young and 53 elderly people. The experiment shows that there is significant difference of all SRs between the young and the elderly, and the system has better performance for objectifying research of CITCM.
基金Supported by Science and Technology Fundation (China University of Geosciences) (No.200520)
文摘This paper presented an online quality inspection system based on artificial neural networks. Chromatism classification and edge detection are two difficult problems in glass steel surface quality inspection. Two artificial neural networks were made and the two problems were solved. The one solved chromatism classification. Hue, saturation and their probability of three colors, whose appearing probabilities were maximum in color histogram, were selected as input parameters, and the number of output node could be adjusted with the change of requirement. The other solved edge detection. In this neutral network, edge detection of gray scale image was able to be tested with trained neural networks for a binary image. It prevent the difficulty that the number of needed training samples was too large if gray scale images were directly regarded as training samples. This system is able to be applied to not only glass steel fault inspection but also other product online quality inspection and classification.
基金Supported by the National Natural Science Foundation of China(No.61073089)the Joint Funds of the National Natural Science,Foundation of China(No.U1304616)the Qinhuangdao Research&Development Program of Science&Technology(No.2012021A044)
文摘A new local cost function is proposed in this paper based on the linear relationship assumption between the values of the color components and the intensity component in each local image window,then a new quadratic objective function is derived from it and the globally optimal chrominance values can be computed by solving a sparse linear system of equations.Through the colorization experiments on various test images,it is confirmed that the colorized images obtained by our proposed method have more vivid colors and sharper boundaries than those obtained by the traditional method.The peak signal to noise ratio(PSNR) of the colorized images and the average estimation error of the chrominance values relative to the original images also show that our proposed method gives more precise estimation than the traditional method.
基金supported by the Korea Research Foundation Grant funded by the Korean Government(MOEHRD),the MKE(The Ministry of knowledge Economy,Korea)the ITRC(Information Technology Research Center)support program(NIPA-2009-(C1090-0902-0007))
文摘General active contour algorithm, which uses the intensity of the image, has been used to actively segment objects. Because the objects have a similar intensity but different colors, it is difficult to segment any object from the others, Moreover, this algodthm can only be used in the simple environment since it is very sensitive to noise. In tinter to solve these problems. This paper proposes an extended active contour algorithm based on a color variance. In complex images, the color variance energy as the image energy is introduced into the general active contour algorithm. Experimental results show that the proposed active contour algorithm is very effective in various environments.
