Segmentation and Extraction of Individual Leaves from Plant Images for Species Classification

ASU Author/Contributor (non-ASU co-authors, if there are any, appear on document)
Dale Garrett Henries (Creator)
Appalachian State University (ASU )
Web Site:
Rahman Tashakkori

Abstract: Plant species classification through the examination of images of plant leaves requires as input an image of a single leaf with no stems or other non-leaf objects. Images of plants, however, usually include more than one leaf, stems, branches, flowers, and other non-leaf objects. For such images each individual leaf needs to be extracted into a unique sub-image, and these sub-images must be cleaned to remove all non-leaf objects. A target leaf could then be selected from the group of sub-images to be provided as the input to the plant species classification program. As a part of the research on this thesis, an algorithm was developed to automate the tasks of detecting and extracting leaf sub-images from plant images and to clean the leaf sub-images by removing all non-leaf objects. To implement the algorithm, software was developed in Java. The proposed algorithm produced at least one perfect leaf result in 18 of the 21 (86%) plant images used in this research, while the remaining three (14%) plant images produced acceptable leaves.

Additional Information

Henries, D.G. (2011). Segmentation and Extraction of Individual Leaves from Plant Images for Species Classification. Unpublished master’s thesis. Appalachian State University, Boone, NC.
Language: English
Date: 2011
Image Processing, Leaf Recognition, Plant Species Classification, Leaf Registration

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