Color and Edge Histograms Based Medicinal Plants' Image Retrieval

In this paper, we propose a methodology for color and edge histogram based medicinal plants image retrieval. The medicinal plants are divided into herbs, shrubs and trees. The medicinal plants are used in ayurvedic medicines. Manual identification of medicinal plants requires a priori knowledge. Automatic recognition of medicinal plants is useful. We have considered medicinal plant species, such as Papaya, Neem, Tulasi and Aloevera are considered for identification and retrieval. The color histograms are obtained in RGB, HSV and YCbCr color spaces. The number of valleys and peaks in the color histograms are used as features. But, these features alone are not helpful in discriminating plant images, since majority plant images are green in color. We have used edge and edge direction histograms in the work to get edges in the stem and leafy parts. Finally, these features are used in retrieval of medicinal plant images. Absolute distance, Euclidean distance and mean square error, similarity distance measures are deployed in the work. The results show an average retrieval efficiency of 94% and 98% for edge and edge direction features respectively.