Contour Extraction based on Circular Hough Transform for Forest Canopy Digital Hemispherical Photography

Abstract

Analysis of forest canopy hemisphere images is one of the most important methods for measuring forest canopy structure parameters. This paper focuses on improvements to contour extraction method for the circular imaging region in forest canopy. We proposed an effective contour extraction algorithm based on circular hough transform for the circular imaging region of digital canopy hemispherical photography (DHP). In order to eliminate the threshold segmentation error, the morphological opening and closing was used to remove these desultory points and smooth the outline of the imaging region. After the boundary points of the imaging area were extracted through erosion, the circular hough transform was applied to fit the boundary point for finding the position of the center and gaining the radius. The experimental results proved its feasibility in terms of effective implementation and robustness.

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“…Circular Hough Transform is a specialized version of Hough Transform that finds circles within an input image. The candidate circular objects are identified by a voting scheme in the Hough parameter space [25]. The circles whose points are intersected the most with the edge points are voted to be a candidate circle in the image.…”