A Review: Plant's Leaf Analysis based on Normalized Features Set using Image Processing
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064



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Review Papers | Electronics & Communication Engineering | India | Volume 7 Issue 1, January 2018

A Review: Plant's Leaf Analysis based on Normalized Features Set using Image Processing

Richa Sharma, Sukhwinder Kaur, Manit Kapoor

Leaf image patterns are the primary characteristics of a plant under the respective category. Pattern image features can be mapped to the respective plant category when made input to a SVM or ANN classifier. Pattern image features in different domains including radial, color, texture, morphological, statistical and ratio domains are extracted out. Image pattern features normalization with respect to size and rotation is an important aspect when made input to classifier. Mean radius is used to normalize the image features with respect to size. Largest chord of the leaf image is approximated to its mid rib, and, rotation aspect is covered by orienting the leaf image with respect to the largest chord i. e. mid rib. Computation of features like radii, area, perimeter and standard deviations in different quadrants contributes fair resolution at close level. Support vector machine classifier categorizes the features set into respective plants class to an equal degree of high accuracy.

Keywords: Image Segmentation, SVM Classifier, Texture Features, Statistical Features

Edition: Volume 7 Issue 1, January 2018

Pages: 1253 - 1255

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How to Cite this Article?

Richa Sharma, Sukhwinder Kaur, Manit Kapoor, "A Review: Plant's Leaf Analysis based on Normalized Features Set using Image Processing", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=ART20179426, Volume 7 Issue 1, January 2018, 1253 - 1255

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