Title: HOG feature and vocabulary tree for Content-based Image Retrieval
Authors: Megha Agarwal, R.P. Maheshwari
Addresses: Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee 247 667, Uttarakhand, India. ' Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee 247 667, Uttarakhand, India
Abstract: Histogram of Oriented Gradients (HOG) feature descriptor is very effective to represent objects and is widely used in human and face detection. In this paper, HOG feature descriptor is applied for Content-based Image Retrieval (CBIR). For handling similarity measurement of large amount of database, vocabulary tree is used. Experimental results illustrate the comparative analysis of retrieval system based on HOG feature descriptor and Gabor transform feature descriptor. It is verified that HOG-based retrieval system improves Average Precision (AP) and Average Recall (AR) (56.75% and 38.45%, respectively) from Gabor-transform-based retrieval system (41.20% and 25.41%, respectively). All the experiments are performed on Corel 1000 natural image database.
Keywords: CBIR; content-based image retrieval; Gabor transform; HOG; histogram of oriented gradients; vocabulary tree; feature descriptors.
International Journal of Signal and Imaging Systems Engineering, 2010 Vol.3 No.4, pp.246 - 254
Published online: 10 Jan 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article