Journal of the Korean Society for Industrial and Applied Mathematics

Korean Society for Industrial and Applied Mathematics (한국산업응용수학회)
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DETECTION AND COUNTING OF FLOWERS BASED ON DIGITAL IMAGES USING COMPUTER VISION AND A CONCAVE POINT DETECTION TECHNIQUE

  • PAN ZHAO (DEPARTMENT OF MATHEMATICS, CHONNAM NATIONAL UNIVERSITY) ;
  • BYEONG-CHUN SHIN (DEPARTMENT OF MATHEMATICS, CHONNAM NATIONAL UNIVERSITY)
  • Received : 2022.12.26
  • Accepted : 2023.03.23
  • Published : 2023.03.25
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Abstract

In this paper we propose a new algorithm for detecting and counting flowers in a complex background based on digital images. The algorithm mainly includes the following parts: edge contour extraction of flowers, edge contour determination of overlapped flowers and flower counting. We use a contour detection technique in Computer Vision (CV) to extract the edge contours of flowers and propose an improved algorithm with a concave point detection technique to find accurate segmentation for overlapped flowers. In this process, we first use the polygon approximation to smooth edge contours and then adopt the second-order central moments to fit ellipse contours to determine whether edge contours overlap. To obtain accurate segmentation points, we calculate the curvature of each pixel point on the edge contours with an improved Curvature Scale Space (CSS) corner detector. Finally, we successively give three adaptive judgment criteria to detect and count flowers accurately and automatically. Both experimental results and the proposed evaluation indicators reveal that the proposed algorithm is more efficient for flower counting.

Keywords

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (2017R1E1A1A03070059).

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