Noise Elimination and Contour Detection Based on Innovative Target Image Contour Coding Algorithm

Siming Meng

doi:10.1155/2020/8895000

Abstract

At present, the image mining is mainly based on its local and key features, which focuses on its texture and statistical grayscale features, but it focuses on its edge and shape features rarely. However, the contour is also an important feature for image shape recognition. In this paper, a good target image contour coding algorithm was adopted, and an LCV segmentation model with good image boundary acquisition capability that can reflect the target image contour features was selected for the original image contour segmentation. The detailed features analysis of the contour coding algorithm was carried out through the experiments; the experimental results showed that the algorithm was a significant technological breakthrough in image feature extraction and recognition.

Highlights

IntroductionThe image mining is based on its texture and statistical grayscale features mostly
At present, the image mining is based on its texture and statistical grayscale features mostly
Compared with other traditional coding algorithms, the proposed algorithm has a unique role in the secondary conversion of image contour features, which can extract the image boundary contour information from multiple perspectives. e detailed featuresanalysis of the contour coding algorithm was carried out through the experiments; the experimental results showed that the algorithm was a significant technological breakthrough in image feature extraction and recognition

Summary

Introduction

The image mining is based on its texture and statistical grayscale features mostly. Several common entropy codes are described briefly as follows: Shannon coding is a coding method called as ShannonFano algorithm obtained by Robert Fano, a mathematics professor from Shannon and MIT based on the information theory proposed by Shannon in 1948∼1949 and it is a kind of symbol coding with variable lengths. When the coding accuracy requirements are relatively similar, this method can be used to compress the data It has the features of strong error diffusion, simplified and fast algorithm, and easy hardware implementation. E detailed featuresanalysis of the contour coding algorithm was carried out through the experiments; the experimental results showed that the algorithm was a significant technological breakthrough in image feature extraction and recognition Compared with other traditional coding algorithms, the proposed algorithm has a unique role in the secondary conversion of image contour features, which can extract the image boundary contour information from multiple perspectives. e detailed featuresanalysis of the contour coding algorithm was carried out through the experiments; the experimental results showed that the algorithm was a significant technological breakthrough in image feature extraction and recognition

Target Image Contour Coding Algorithm

Feasibility Analysis of Target Image Contour Coding Algorithm