Plant Leaf Analysis Based on Color Histogram and Cooccurrence Matrices - Londhe, Renuka R (International Journal of Computer Sciences and Engineering, 2019)
Automatic identification of plant is very useful for environmentalists, natural scientists, biologists, food engineers, amateur botanists, educators and doctors (Ayurvedacharya). In this paper a computer based application was developed to automatically identify herbal plant type by the photographs of plant leaves. The leaf image used for analysis can be either a database digital image or photograph recorded by camera. The image used was of single leaf with light and white background. The leaf image analysis has been performed with MATLAB 2016. The procedure comprised of analysis of leaf image segmentation, feature extraction from Shape, Color histogram and Cooccurrence Matrices respectively. Shape of leaf is the furthermost widespread feature used in identification. The Leaf analysis has been performed for 25 herbal medicinal plant leaves from Folio database. The Shape feature was extracted using edge detection operator Sobel; and to record the color statistical features, color histogram and co-occurrence matrices with statistical parameters. The results of this article will be useful to identify the leaves of different types of plants.