Rafflesia Khan and Rameswar Debnath, Khulna University, Bangladesh

Leaf detection and segmentation is a complex image segmentation problem as leaves are most often found in groups with natural background. Edges of leaves cannot be clearly defined from image because of their color similarities.Also,separating every single as well as overlapping leaf individually is even more challenging as leaves share almost same color, texture and shape. In this paper, we propose a new automatic approach for leaf segmentation from image. Our leaf segmentation process uses efficient techniques for processing an image to obtain contours of every individual objects. Then, it selects the best appropriate connected contours that represent region of every leaves appearing in an image. Our model archives an overall 90.46% segmentation rate where segmentation rates for single and overlapping leaves are 95.34% and 86.73%, respectively.

image processing, leaf object segmentation, overlapping leaves, connected contour, object boundary detection.