Light leaf spots segmentation algorithm based on colour difference vectors. (2nd March 2023)

• Record Type: Journal Article
• Authors: Miao, Sheng; Kou, Weili; Zhong, Lihui
• Is Part Of: International journal of innovative computing and applications. Volume 14:Number 1/2(2023)
• Page Start: 12
• Page End: 21
• Publication Date: 2023-03-02
• Subjects: light leaf spots -- image segmentation -- vein removal -- colour difference vector; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

For plant diseases monitoring and diagnosing, leaf spots image segmentation and quantification is very crucial. Compared with dark spots, light leaf spots segmentation is hindered by the unobvious colour and similar leaf veins. This study specially focuses on the light leaf spots segmentation and vein removals. Firstly, vein and spot masks were respectively extracted from healthy and spots leaves by using a mask extraction model presented in this study. Secondly, vein ratio of vein masks was calculated to evaluate whether vein removal is needed or not. Thirdly, vein area and roundness were calculated for both vein and spots masks, and areas with high similarity to veins were removed from spots mask. The proposed algorithm was tested using leaves with light spots of 12 plants types. The results show that the presented algorithm has higher average accuracy (86%) than both traditional watershed (77%), Barbedo (2017) (82%) and CNN (81%).