Three dimensional fragment category detection method based on histogram feature kernel optimized discriminant analysis

Abstract

The invention discloses a three dimensional fragment category detection method based on histogram feature kernel optimized discriminant analysis, relating to a three dimensional fragment category detection method. The invention solves the problem of inaccurate detection existing in the present three dimensional fragment category detection methods. The category detection method comprises the following steps of: scanning a fragment to be detected to obtain three dimensional surface data of the fragment; carrying out feature extraction on the three dimensional surface data of the fragment, obtained in the step 1 to obtain a three dimensional surface feature vector of the fragment; carrying out kernel optimized discriminant analysis on the three dimensional surface feature vector of the fragment, obtained in the step 2 to obtain a feature vector of kernel optimized discriminant analysis; and finally utilizing a nearest neighbour classification to carry out category detection on the feature vector of kernel optimized discriminant analysis, obtained in the step 3 to obtain the category of the fragment. The invention overcomes the insufficiencies of the prior art, can accurately detect the category of the three dimension fragment and can be applied to the technical field of category detection, classification and the like of the three dimensional fragment.

Description

technical field [0001] The invention relates to a category detection method of three-dimensional fragments. Background technique [0002] At present, the splicing of cultural relics remains at the manual level, relying only on historical records and written records, and is completed by professionals based on experience. The preservation of cultural relics based on manual stitching faces the defects of long cycle, strong subjectivity, and poor repeatability, and work mistakes may cause immeasurable damage to cultural relics. With the continuous development of computer technology, it has effectively promoted the development of computer graphics processing, pattern recognition, and three-dimensional information processing technology, making digital splicing of historical relics possible. The 3D surface of damaged cultural relics is converted into digital form by specific digital acquisition equipment such as 3D scanners, digitizers, and profilers, and input into the computer, ...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to solve the problem of inaccurate detection in the current three-dimensional debris category detection method, and to provide a three-dimensional debris category detection method based on histogram feature kernel optimization discriminant analysis

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