Leaf identification for the extraction of medicinal qualities using image processing algorithm

Abstract

Plants are in need nowadays in human life. There are certain plants which are prone with medicinal qualities by nature. Many medicinal plants have a medicinal quality from root to leaf. Leaves play major role in our ecosystem. Identifying the leaf from look-alike is becoming a major task in our day to day life. Since there is a mistake in human vision for medicinal leaf with lookalike leaf computer vision is required. In these days identifying leaf is not possible. Therefore computer technique is must in identifying them. Image processing plays a vital role in leaf identification. A database is created with 127 herbal leaves. For creating a database 11 texture parameters are taken into account. The parameters are Sum of Variance, Inverse Difference Moment, Aspect ratio, Correlation, Sum Entropy, Mean, and Sum Average. Gray level co-occurrence matrix (GLCM) is used for determining the parameters like entropy, homogeneity, contrast and energy. A test image is taken and compared with the database; the dissimilarity is calculated with the extracted parameters. The one with least dissimilarity is identified as the leaf and the output is displayed.