Title: A novel spatial domain enhancement based image segmentation method with mean shift filtering and automated thresholding for leaf images on natural background

Authors: Muhammed Shafi Koodakkal; Mohammed Ismail Bellary; Narayanan Sarala Sreekanth

Addresses: Department of Information Technology, Kannur University, Mangattuparamba, India ' Department of Information Technology, Kannur University, Mangattuparamba, India ' Department of Information Technology, Kannur University, Mangattuparamba, India

Abstract: Identification of plants is essential for the production of fuel, healthy foods, medications, animal feed, and biodiversity conservation. It is difficult to recognize all of the plant species available in the world and identify some features that can be used to classify different plant species. Plant recognition relies on the shape and colour features of the leaves. The segmentation of a region from an image depends on background complexity. It will be simpler if the leaf is on a light background, and more challenging on a natural background. We proposed a method for the segmentation of leaf images on a natural background. One deep convolutional neural network has also trained to segment leaves from four different datasets. Through experimental runs, the obtained results show that our method achieves an accuracy rate of 98% and high PSNR and low RMSE scores, which is significantly better than the current state-of-the-art methods.

Keywords: image segmentation; enhancement; mean shift filtering; mask RCNN.

DOI: 10.1504/IJCVR.2026.156203

International Journal of Computational Vision and Robotics, 2026 Vol.17 No.3, pp.273 - 296

Accepted: 04 May 2024
Published online: 08 Sep 2026 *

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