Feature Detection Algorithm for Moving Objects Based on Gray Histogram

doi:10.3969/j.issn.1006-2475.2019.06.012

Abstract

Abstract: In order to improve the detection effect and guidance of moving targets, a feature detection algorithm based on gray histogram analysis is proposed. The moving object image is collected and the visual feature is analyzed by using the visual imaging technology, and the dynamic visual feature quantity of the moving object is extracted. The feature separation of the moving image is carried out according to the moving object edge differential transform and the spatial position relation, and the edge contour feature of moving object image is extracted. The binary separation of moving object image is carried out by using statistical shape model, and the gray histogram of moving object image is constructed. According to the statistical information of gray histogram, the object feature detection and dynamic feature extraction are carried out to realize the visual detection and dynamic recognition of moving target image. The key features of moving object are extracted effectively and the target feature detection is realized. The simulation results show that the proposed method has better performance in feature detection of moving target images and dynamic recognition ability for moving targets.

Key words: moving image, moving object, target feature detection

CLC Number:

TP391

LU Xing-hua, LIU Ming-yuan, LONG Qing-jia, CHEN Ze-jiang. Feature Detection Algorithm for Moving Objects Based on Gray Histogram[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2019.06.012.

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