Classification of Plants Using Images of their Leaves

ASU Author/Contributor (non-ASU co-authors, if there are any, appear on document)
Biva Shrestha (Creator)
Institution
Appalachian State University (ASU )
Web Site: https://library.appstate.edu/
Advisor
Rahman Tashakkori

Abstract: Plant recognition is a matter of interest for scientists as well as laymen. Computer aided technologies can make the process of plant recognition much easier; botanists use morphological features of plants to recognize them. These features can also be used as a basis for an automated classification tool. For example, images of leaves of different plants can be studied to determine effective algorithms that could be used in classifying different plants. In this thesis, those salient features of plant leaves are studied that may be used as a basis for plant classification and recognition. These features are independent of leaf maturity and image translation, rotation and scaling and are studied to develop an approach that produces the best classification algorithm. First, the developed algorithms are used to classify a training set of images; then, a testing set of images is used for verifying the classification algorithms.

Additional Information

Publication
Thesis
Shrestha, B. (2010). Classification of Plants Using Images of their Leaves. Unpublished master’s thesis. Appalachian State University, Boone, NC.
Language: English
Date: 2010
Keywords
Plants Classification , Pattern Recognition, Leaf Recognition, Feature Extraction, Skeletonization

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