Research on the algorithm counting tea pests by image in complex background

doi:10.14088/j.cnki.issn0439-8114.2021.20.032

Abstract

Abstract: Based on a kind of insect trap lamp equipment, the sample images gained and the counting algorithms with image processing were addressed. Adopted some common algorithms of separating background areas, such as color histogram segmentation and gray threshold segmentation, the sample images were difficult to be separated. This paper develops an image processing algorithm which depend on grid division. Segmented the image as 10×10, and then extracted the pests areas from the separated images. For the overlapping areas will affect the accuracy of counting, developed the marker-controlled watershed segmentation algorithm. Marking the image with minimum extension transform to segment the overlapping areas and then realizing the pests counting, the noise test and counting test were developed furtherly. Experimental results showed that, for the sample images which collected from this kind of pests trap equipment, the average accuracy of the algorithm was 91.8%. This algorithm could extract the pests areas from the sample image completely and segment the overlapped pests effectively. And the algorithm was applicable for tea pests counting in complex background.

Key words: tea pests, image processing, overlap, background area separation, counting

CLC Number:

HUANG Can-can, CHEN Ya-long, ZHANG Wei, CAI Qiang. Research on the algorithm counting tea pests by image in complex background[J]. HUBEI AGRICULTURAL SCIENCES, 2021, 60(20): 158-163.

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