Flower Classification using Texture and Color Features

Abstract

In this research paper, we have used texture and color features for flower classification. Standard database of flowers have used for experiments. The pre- processing like noise removal and segmentation for elimination of background are apply on input images. Texture and color features are extracted from the segmented images. Texture feature is extracted using GLCM (Gray Level Co-occurrence Matrix) method and color feature is extracted using Color moment. For classification, neural network classifier is used. The overall accuracy of the system is 95.0 %.