Dimensionality Reduction Based On The Color Of Color Image Edge Detection

Edge is the most fundamental characteristic of the image which exists in irregular structure and unstable phenomenon.In other words, it exists in the abrupt change of signal. These points not only transferred most image information but also gave an concrete location of image outline. These outlines are very important in image processing. In computer vision, edge detection is an essential step in gaining the important characteristics of objects. Edge detection has decreased data amount by a large margin, got rid of the irrelevant information, reserved the important structure attribute of image, and established a basis for future work. As the fundamental step of the image analysis and understanding, the accuracy and reliability of edge detection make the computer vision affect the understanding of the objective world directly. At present, most of the old methods applied to grayscale images, the research of edge detection algorithm for color image is far from mature than gray ones.This thesis first summarized the methods of edge detection and make a contrast among these classical edge detection operators. On the basis of introduction of the color space, we classify the methods into many categories, such as classical edge detection operators method, multi-dimension grads method, vector space method and so on, then make a research on them. On the basis of theses, the main works are as follows:(1) RGB space is the most common space for expressing the color information. Color image is usually stored and expressed in the form of RGB. According to the characteristics of RGB color space, we constructed the color triangle of a pixel using its color coordinates, and consequently calculate the perimeter and the internal angle of the color triangle. The perimeter and the internal angle of the triangle can be seen as the information measurement of a pixel. It can determine whether a pixel is the edge point of a color image by computing the information quantity of a pixel in its neighborhood. We transformed the color information from three-dimensional space to two-dimensional space, defined the measure of color information of pixel in two-dimensional space. Experimental results indicate that the method in this paper can be realized easily, and can detect more legible edges than the traditional method.(2) HSI color space starts from human visual system, uses hue, saturation, and intensity to describe color. HSI color space is more suitable for human visual properties than RGB color space. A large number of algorithms can be used in HSI color space conveniently. This three components are independently and can be treated separately. Through analyzing the characteristics of HSI space, we proposed a method as follows:It can construct the color triangle of a pixel using its color coordinates. S and I are two edges of the triangle. H is an angle between the two edges. Then we can gain the triangle area and edge length. The color, triangle area and shape can change with any change of H, S, I value. It can determine whether a pixel is a edge point of color image by the information of area or edge length. Compared with the picture edge classical edge operator, the new one is clearer and more intact.