Edge Location Method for Multidimensional Image Based on Edge Symmetry Algorithm

Chen Li,Chinmay Chakraborty

doi:10.1155/2021/1326357

Abstract

The most basic feature of an image is edge, which is the junction of one attribute area and another attribute area in the image. It is the most uncertain place in the image and the place where the image information is most concentrated. The edge of an image contains rich information. So, the edge location plays an important role in image processing, and its positioning method directly affects the image effect. In order to further improve the accuracy of edge location for multidimensional image, an edge location method for multidimensional image based on edge symmetry is proposed. The method first detects and counts the edges of multidimensional image, sets the region of interest, preprocesses the image with the Gauss filter, detects the vertical edges of the filtered image, and superposes the vertical gradient values of each pixel in the vertical direction to obtain candidate image regions. The symmetry axis position of the candidate image region is analyzed, and its symmetry intensity is measured. Then, the symmetry of vertical gradient projection in the candidate image region is analyzed to verify whether the candidate region is a real edge region. The multidimensional pulse coupled neural network (PCNN) model is used to synthesize the real edge region after edge symmetry processing, and the result of edge location of the multidimensional image is obtained. The results show that the method has strong antinoise ability, clear edge contour, and precise location.

Highlights

In view of the shortcomings of the above two methods, this paper proposes an edge location method for the multidimensional image based on edge symmetry algorithm to improve the accuracy of edge location for the multidimensional image. is model was defined and tested for pictures in order to assess the performance of the suggested model
In order to verify the accuracy of edge location for multidimensional images, the proposed method is compared with the subpixel method and the spatial distance method
In view of the above analysis and discussion, this paper proposes an edge location method for the multidimensional image based on edge symmetry, which can process the multidimensional image with strong antinoise and can locate the multidimensional image’s edge more precisely and clearly, and the effect is obvious. e analysis is from the following three aspects: (1) In this paper, a Gauss filter is introduced to preprocess multidimensional images. e problem of spatial distance weighting and pixel gradient is well solved by the Gauss filter. e pixel gradient reflects the image edge features, which is very helpful for multidimensional image’s edge location

Summary

Introduction

Symmetry is a common feature of many natural objects and artificial phenomena It is widely used in image processing to describe the shape features of objects. Spatial moment location is a common method in a fixed background It can generally provide complete edge data, but its location effect depends on the merits of background model updating algorithm. E subpixel location method has strong adaptability to scene changes, but, generally, it cannot locate all the relevant edge pixels completely. It produces holes in the image entity, and it is easy to miss the location of some image edges [6]. The image is preprocessed to improve the image quality; secondly, the edge gradient in the edge region of the multidimensional image is calculated by using the vertical direction of the Sobel operator [7]; the candidate region is determined according to the characteristics of large jump and the large number of edge changes between the edge and the background

Results

Discussion

Conclusion