Individual plant extraction and counting from field images based on leaf matching
1. College of Mathematics and Informatics, South China Agricultural University, Guangzhou， Guangdong 510642, China; 2. Guangxi Key Laboratory of Biology for Crop Diseases and Insect Pests/Institute of Plant Protection, Guangxi Academy of Agricultural Sciences, Nanning， Guangxi 530007, China
Abstract：A method was constructed to extract individual plant image from the continuouslycollected images. The leaf surface region segmentation was obtained， and the individual plant image was separated based on leaf surface image by leaf distance. The two consecutive adjacent images were stitched together, and the newlyformed images were transformed and stitched with empty images to produce individual plant image for determining the centroid. The distance between the centroid of all stitched images in the previous image and the centroid of all the stitched images in the subsequent image was compared. The distance threshold method was used to identify whether the two images were the images of the same crop. Transfer closure was applied for obtaining the plant image set of each crop in multiple continuous images, and the image closest to the center was selected as the best image. Five crops were used to verify the proposed method. The results show that the accuracy of plant number reaches 100%. The proposed method can successfully and precisely extract individual plant image with high computational efficiency.
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