Efficient image retrieval through hybrid feature set and neural network

Images are an important part of daily life. The huge repository of digitally existing images cannot be easily controlled by any individual. Extensive scanning of the image database is very much essential to search a particular image from the huge repository. In some cases, this procedure becomes very exhaustive also. As a result, if a count of ten thousand, lakhs or considerably more images are included in image database, then it may be transformed into a tedious and never ending process. Content-based image retrieval (CBIR) is a technique, which is used for retrieving any image. This type of image retrieval procedure is centred on the actual content of image. This paper proposed a model of hybrid feature set of Haar wavelets and Gabor features and analysed with different existing models image retrieval. Content based image retrieval using hybrid feature set of Haar wavelets and Gabor features superiors on other models.