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Apple Image Segmentation Model Based on R Component with Swarm Intelligence Optimization Algorithm

Volume 14, Number 6, June 2018, pp. 1149-1160
DOI: 10.23940/ijpe.18.06.p6.11491160

Liqun Liua and Jiuyuan Huob

aCollege of Information Science and Technology, Gansu Agricultural University, Lanzhou, 730070, China
bSchool of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China

(Submitted on March 11, 2018; Revised on April 21, 2018; Accepted on May 28, 2018)


Because of large numbers interference factors such as complex background in apple images in natural scene, it is difficult to achieve good image segmentation results. To solve these problems, the color apple image segmentation method under natural scenes is modeled, and an apple image segmentation model based on R component with swarm intelligence optimization algorithm (AISM-RSIOA) is constructed to achieve the initial and secondary segmentation of the images. Under the six conditions of direct sunlight with strong, medium and weak illumination, and backlighting with strong, medium and weak illumination in natural scenes, the images segmentation experiments were taken on a series of mature HuaNiu apple images. The results of initial segmentation showed that the ISMR method has the optimal segmentation effect, and the segmentation success rates achieve 100.0%. In the secondary segmentation stage, the fruits can be fully separated from the background by using the improved threshold segmentation method. The segmentation results demonstrated that the model can effectively improve segmentation effect of images.


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