A brief review of color matching technology and its application of printing RGB images by CMY or CMYK ink jet printers is presented, followed by an explanation to the conventional approaches that are commonly used in ...A brief review of color matching technology and its application of printing RGB images by CMY or CMYK ink jet printers is presented, followed by an explanation to the conventional approaches that are commonly used in color matching. Then, a four color matching method combining neural network with genetic algorithm is proposed. The initial weights and thresholds of the BP neural network for RGB to CMY color conversion are optimized by the new genetic algorithm based on evolutionarily stable strategy. The fourth component K is generated by using GCR (Gray Component Replacement) concept. Simulation experiments show that it is well behaved in both accuracy and generalization performance.展开更多
Conventional correlation matching algorithms waste great time in invalid area search. This paper proposes a color tracking method based on correlation search area optimization on target characteristic hue decision. By...Conventional correlation matching algorithms waste great time in invalid area search. This paper proposes a color tracking method based on correlation search area optimization on target characteristic hue decision. By quantifying and reducing dimensions of HSV（ hue saturation value） color space, a one-dimensional hue space is constructed. In the space, the target characteristic hue granule set is constructed, which contains attributes such as value, area and average distance between pixels and aiming center. By using granular computing method, the similarity between target and search blocks is obtained and the invalid search areas can be removed. The color tracking experiment has proved that the algorithm can improve real time performance for conventional matching algorithms without precision lost.展开更多
A closed-loop algorithm to detect human face using color information and reinforcement learning is presented in this paper. By using a skin-color selector, the regions with color "like" that of human skin ar...A closed-loop algorithm to detect human face using color information and reinforcement learning is presented in this paper. By using a skin-color selector, the regions with color "like" that of human skin are selected as candidates for human face. In the next stage, the candidates are matched with a face model and given an evaluation of the match degree by the matching module. And if the evaluation of the match result is too low, a reinforcement learning stage will start to search the best parameters of the skin-color selector. It has been tested using many photos of various ethnic groups under various lighting conditions, such as different light source, high light and shadow. And the experiment result proved that this algorithm is robust to the vary-ing lighting conditions and personal conditions.展开更多
A novel approach is proposed to automatically detect pomographic images with skin-like color background on the Intemet using the locations of human faces and bodies. It has two separate skin-color detection steps： th...A novel approach is proposed to automatically detect pomographic images with skin-like color background on the Intemet using the locations of human faces and bodies. It has two separate skin-color detection steps： the first one is to quickly detect the potential human skin-color regions; and the second one is to use an off-the-shelf face detector to locate a human face and then apply hypothesis testing based on series of assumptions which take into account the face-height ratio, body orientation and modem photograph composition common sense, etc. After that, a template matching method is used to further discriminate normal images or pornographic ones. Experimental results show that the proposed method has high precision and real time speed.展开更多
文摘A brief review of color matching technology and its application of printing RGB images by CMY or CMYK ink jet printers is presented, followed by an explanation to the conventional approaches that are commonly used in color matching. Then, a four color matching method combining neural network with genetic algorithm is proposed. The initial weights and thresholds of the BP neural network for RGB to CMY color conversion are optimized by the new genetic algorithm based on evolutionarily stable strategy. The fourth component K is generated by using GCR (Gray Component Replacement) concept. Simulation experiments show that it is well behaved in both accuracy and generalization performance.
文摘Conventional correlation matching algorithms waste great time in invalid area search. This paper proposes a color tracking method based on correlation search area optimization on target characteristic hue decision. By quantifying and reducing dimensions of HSV（ hue saturation value） color space, a one-dimensional hue space is constructed. In the space, the target characteristic hue granule set is constructed, which contains attributes such as value, area and average distance between pixels and aiming center. By using granular computing method, the similarity between target and search blocks is obtained and the invalid search areas can be removed. The color tracking experiment has proved that the algorithm can improve real time performance for conventional matching algorithms without precision lost.
文摘A closed-loop algorithm to detect human face using color information and reinforcement learning is presented in this paper. By using a skin-color selector, the regions with color "like" that of human skin are selected as candidates for human face. In the next stage, the candidates are matched with a face model and given an evaluation of the match degree by the matching module. And if the evaluation of the match result is too low, a reinforcement learning stage will start to search the best parameters of the skin-color selector. It has been tested using many photos of various ethnic groups under various lighting conditions, such as different light source, high light and shadow. And the experiment result proved that this algorithm is robust to the vary-ing lighting conditions and personal conditions.
文摘A novel approach is proposed to automatically detect pomographic images with skin-like color background on the Intemet using the locations of human faces and bodies. It has two separate skin-color detection steps： the first one is to quickly detect the potential human skin-color regions; and the second one is to use an off-the-shelf face detector to locate a human face and then apply hypothesis testing based on series of assumptions which take into account the face-height ratio, body orientation and modem photograph composition common sense, etc. After that, a template matching method is used to further discriminate normal images or pornographic ones. Experimental results show that the proposed method has high precision and real time speed.
