Construction method of shape descriptor and image retrieval method based on descriptor

Abstract

The invention discloses a construction method of a shape descriptor and an image retrieval method based on the descriptor. The construction method of the shape descriptor comprises the following steps: (a) describing a triangular space relationship between two adjacent sampling contour points and a shape mass center by using an only K value, and combining a K value histogram obtained according to K value distribution and a mass center distance histogram obtained according to the distance between the contour points and the shape mass center to construct a new shape descriptor based on contour; (b) clustering the shape contour points, taking the obtained clustering center as new feature points, taking the feature of a clustering region as the feature value of the corresponding feature points, describing a triangular space relationship of the feature of the combined objects between any two new feature point objects and a reference object by using an only L value, and constructing a new shape descriptor based on a region by using one group of L values obtained by each shape and 4-step Zernike matrix; and (c) composing the shape descriptor of the invention by the descriptors based on contour and region. Based on the shape descriptor of the invention, the invention further provides the image retrieval method.

Description

technical field [0001] The present invention relates to a descriptor construction method and image retrieval technology for feature extraction, more specifically, a shape descriptor construction method for shape feature extraction and an image retrieval method based on shape descriptors. Background technique [0002] Shape is one of the most important characteristics of an object. It plays an important role in human visual perception and has a wide range of applications in many computer vision fields, such as object classification, object recognition, and object retrieval. Shape descriptors are used to describe shape features and are generally divided into contour-based shape descriptors and region-based shape descriptors. [0003] Commonly used contour-based shape descriptors generally only represent the characteristics of a single contour point, and seldom consider describing the spatial characteristics between two adjacent contour points. In the non-patent literature (H...

AI Technical Summary

Problems solved by technology

Among them, the Zernike moment can effectively describe the global information of the shape, but it cannot effectively distinguish the deformation of the small contour

Feature points such as corner points can effectively describe the place where the contour changes drastically, but because it is extracted based on the window of its surrounding area, there are defects such as a large number and poor noise resistance

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