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Machine Learning Theory and Practice, 2022, 3(1); doi: 10.38007/ML.2022.030104.

Infrared Laser Image Feature Localization Technology Based on Decision Tree Algorithm

Author(s)

Xiangdong Ma

Corresponding Author:
Xiangdong Ma
Affiliation(s)

Heilongjiang Shicheng Education Consulting Office, Harbin 150040, China

Abstract

Because infrared small target image has the characteristics of low signal-to-clutter ratio, small size of target and no obvious shape structure and texture information, it is difficult to detect small target in infrared system. Therefore, it is of practical significance to study the key and difficult points of infrared detection. This paper mainly studies the feature localization technology of infrared laser image based on decision tree algorithm. This paper first analyzes the basic theory of feature image matching, focusing on the performance of the classical edge feature extraction, point feature extraction and description methods. In this paper, the decision tree method is applied to the field of infrared dim small target detection, considering the perspective of image segmentation, to explore the ability of decision tree to express infrared image targets.

Keywords

Decision Tree Algorithm, Infrared Image, Laser Image, Feature Localization

Cite This Paper

Xiangdong Ma. Infrared Laser Image Feature Localization Technology Based on Decision Tree Algorithm. Machine Learning Theory and Practice (2022), Vol. 3, Issue 1: 27-34. https://doi.org/10.38007/ML.2022.030104.

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