Experiments on content based image classification using Color feature extraction

Content based classification approach is becoming necessary to support the retrieval and indexing of images. This paper uses Color features of an image to form a feature vector on which data pre-processing is applied. These features are then used by machine learning classifiers to classify the images. Classification accuracy is evaluated in two color spaces and image sizes. Empirical results show that a high classification accuracy can be achieved even with highly complex nature of data.