ABSTRACT
The increase of the digital content on the web is tremendous, not only in volume but also in a variety of platforms by which it is created and added to the digital world, i.e., the internet. This chapter proposed a scheme to identify the category of different image classes depending upon the given query made by the user. Here the chapter proposed a Novel Semantic Feature Generation Algorithm (NSFGA) which purely depends on semantic attributes of the images. This approach is based on a technique to extract semantic features from different classes from images by sliding window, and it is performing a whole scanning of the query image and produces an output which will be the identified category from the different class of image dataset. Here our implementation includes repeated scanning of the image so that the accuracy should be optimum. This project uses the Support Vector Machine (SVM) to identify the required category by training and testing dataset.
