Contour Points based P2P Algorithm for Shape Matching and Image Retrieval

Abstract

Based on the extracted contours of objects from images, one point to point (P2P) method is proposed for shape matching and image retrieval. Taking contour of one object as reference, contour of another object is transformed to reach their best match, during which the similarity is evaluated by comparison of two corresponding sets of contour points. Translation, scaling and rotation are all considered in transformation, thus the algorithm is robust to objects with different position, size and posture. The experimental results are presented and compared with those from two popular shape based techniques, Hu invariant moments and Zernike moments. Performance of our new approach has proved its efficiency in both matching accuracy and computational expense, and it can be used in related applications together with the other kinds of shape features or even color features, texture features, etc.

Analysis and tracking of animal movements through granulation of temporal domain (GTD)

“…The proposed method creates motion image from con-secutive pair of frames. For this, moving object extracts from frame 1, as at frame 0 there is no reference image [4]. Through this continual process, motion would be estimated based on previous image.…”

Image Retrieval System Using Intuitive Descriptors

“…Same method can be used for color image retrieval though it will be of less efficient as whole image color is represented by one pixel only. Algorithm of contour points based point to point matching, statistical projection based algorithm based image retrieval and Robert algorithm are the field of applications for the image retrieval [12][13][14].…”