The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The paper suggests a novel approach for visual key-points description. Our approach is basically integrate the descriptors of local features (e.g. SURF (Speeded Up Robust Features)) and HOG (Histograms of Oriented Gradients) using patch-based integration to enhance the distinctness between image objects. It was tested in the context of image categorization using bag of features model. The experimental results on Caltech101 dataset with 7 categories show that the proposed approach achieve the best performance over several state-of-art approaches. Also this paper investigate the impact of HOG patch-based integration on these methods in terms of accuracy and computational overhead.