Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/7327
Title: Automatic Identification of Licorice and Rhubarb by Microscopic Image Processing
Authors: Fataniya, Bhupendra
Joshi, Meet
Modi, Urmil
Zaveri, Tanish
Keywords: Moments
Segmentation
Compactness Parameter
SVM Classifier
ROC Curve
EC Faculty Paper
Faculty Paper
ITFEC030
ITFEC008
Issue Date: 2015
Publisher: Science Direct
Citation: Second International Symposium on Computer Vision and the Internet (VisionNet’15)
Series/Report no.: ITFEC030-6;
Abstract: This paper presents a method for automatic identification of Herbal Plants Licorice and Rhubarb by microscopic image processing. This method is useful for identifying species from fragments or powders and for distinguishing species with similar morphological characteristics. In first step, desired region of the image is cropped by intensity based segmentation. After that Hu’s moments and compactness parameters are calculated for cropped part which are rotational, scaling and shift invariant. In the final stage using SVM classifier, classify the herbal plants of licorice and rhubarb. Area under the ROC curve for licorice is 0.7051 and for rhubarb it is 0.9487.
Description: Procedia Computer Science Vol. 58, 2015, Page No. 723 - 730
URI: http://hdl.handle.net/123456789/7327
ISSN: doi: 10.1016/j.procs.2015.08.093
Appears in Collections:Faculty Papers, EC

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