Image Retrieval Based On Edge Detection And Goal Location

Content-Based Image Retrieval (CBIR) is an important research field in the development of image retrieval. It is an effective method of administering magnanimity digital image and video information. Its essence is to realize the image automatic search utilizing the special understanding way of the image. It can be used to realize one-to-many similar search.This paper mainly studies retrieval algorithm based on image edge and color features. The main contents include:First of all, the technology of CBIR was simply introduced. A great deal of methods of extraction and expression about the color, texture and shape features were summed up and summarized in detail. Image segmentation and pixels classifying of image retrieval pretreatment was studied. The limitation and deficiency of the existing retrieval algorithm was analyzed.Second, two image retrieval algorithms using image edge structure and color features were put forward. (1) Image Retrieval Based on Canny Edge Detection and Goal Location. (2) Image Retrieval Based on the Wavelet Transform Edge Detection and Goal Location. The edge feature was described and extracted in the two kinds of domains: the spatial domain and the transform domain. The images that have the close correlation edge to the example image was searched to form a new multi-images database. Then it used the dominant color to divide image target, used effective target part for similarity matching and finishing the retrieval of the example images. Experiments show that this kind of arithmetic can well and efficiently detect the edge feature and improve the efficiency.The edge detection was used to reflect the geometrical structural feature, not being the method of image segmentation. And the wavelet transform was introduced, which can avoid the difficulty of image understanding, efficiently show the distribution of image structure and improve the noise immunity in image retrieval.