Base and apex angles and margin types-based identification and classification from medicinal plants' leaves images. (1st January 2013)

• Record Type: Journal Article
• Authors: Nandyal, Suvarna S.; Anami, Basavaraj S.; Govardhan, A.
• Is Part Of: International journal of computational vision and robotics. Volume 3:Number 3(2013)
• Page Start: 197
• Page End: 224
• Publication Date: 2013-01-01
• Subjects: angle-based -- medicinal leaf -- leaf segmentation -- widest part -- leaf margin -- Otsu; Computer vision -- Periodicals; Robotics -- Periodicals; Artificial intelligence -- Periodicals; 006.3705
• Languages: English
• ISSNs: 1752-9131

Abstract

In this paper, we have proposed a method for medicinal plants identification and classification from their leaves images based on base angle, apex angle and margin type. In Ayurveda, medicines are extracted from leaves, roots and stems. Many a times, the plants are recognised by their leaves. Therefore, we have considered leaves images in this work. Adoptive Otsu threshold method is used for segmentation of leafy part from the background. The database includes altogether 900 leaves images representing 18 shapes with different base and apex angles and margins. The leaf images are classified based on features such as widest part of leaf and its location, stem angle, base angle and margin. The two angles and margin features are extracted using trigonometric and chain code approaches respectively. The proposed approach is robust, position, scale and rotation invariant and works for even tender leaves. The average recognition and classification accuracy of 98% is obtained. The work assists novice users of Ayurvedic practitioners.