Root Image Edge Detection Based on Improved Gray Correlation Degree

LENG Xin, SONG Wen-long

Packaging Engineering ›› 2016 ›› Issue (15) : 46-49.

Packaging Engineering ›› 2016 ›› Issue (15) : 46-49.

Root Image Edge Detection Based on Improved Gray Correlation Degree

  • LENG Xin, SONG Wen-long
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Abstract

In order to calculate and analyze the basic parameters of plant root system, an improved gray correlation degree edge detection algorithm was proposed by acquisition technique for array distributed endoscopic image. Based on the grey relational analysis theory, the algorithm adopted the variable weight model, took the two templates of Sobel operator as the reference sequence, selected the eight neighborhood component values of pixels to form a comparison sequence and realized the edge detection by the correlation degree between the two kinds of sequences. The simulation results showed that the proposed algorithm was able to accurately test the useful information of the root edge compared with the traditional algorithm. In conclusion, the edge detection algorithm of variable weight correlation degree based on Sobel operator can effectively improve the edge detection effect, and has a certain anti noise performance.

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LENG Xin, SONG Wen-long. Root Image Edge Detection Based on Improved Gray Correlation Degree[J]. Packaging Engineering. 2016(15): 46-49

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