期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2016
卷号：9
期号：10
页码：109-126
出版社：SERSC
摘要：Immature greencitrus fruit detection using conventional color imagesis a challenging task due to fruit color similarity with the background, partial occlusion, varying illumination and shape irregularity. Therefore, most existing green fruits detection algorithms, which use color as the main discriminant feature, have a low recognition rate and ahigh rate of false positives. In this manuscript, we developed a novel Green Citrus fruit Detection algorithm based on the proposed Reticulate Grayladder Feature (GCDRGF), which contained 4 major steps: First, an 8-graylevel image was generated by the preprocessing steps of median filtering, histogram-based equalization and 8-graylevel discretization of the input raw image. Secondly, reticulate grayladders were obtained by a multidirectional scanning on the 8-graylevel image, and rule-based pseudo-grayladder removal strategies were used to remove false positives of target grayladders. Thirdly, grayladder clustering and fruit location fitting were used to generate candidate regions for target fruits. Finally, majority voting was performed to determine the results of candidate regions based on the analysis of apparent features and recticulate grayladders within candidate regions. The experimental resultsproved the effectiveness ofthe proposed reticulate grayladder feature and the corresponding detection algorithmwith respect to variousilluminantand imagingconditions. Compared with the existed eigenfruit algorithm, ouralgorithmhasa higher rate of successful recognition and alower rate of false positives, which helpsto greatly improve the productivity of robotic operations.
关键词：reticulate g;ray;ladder feature;s; green citrus detection; image segmentation
