Sketch-based Image Retrieval using Rotation-invariant Histograms of Oriented Gradients
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2017 by IJCTT Journal|
|Year of Publication : 2017|
|Authors : Y.Jhansi, Dr.E.Sreenivasa Reddy|
|DOI : 10.14445/22312803/IJCTT-V49P118|
Y.Jhansi, Dr.E.Sreenivasa Reddy "Sketch-based Image Retrieval using Rotation-invariant Histograms of Oriented Gradients". International Journal of Computer Trends and Technology (IJCTT) V49(2):121-124, July 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
This paper presents a novel approach for sketch-based image retrieval based on Rotation Invariant. The approach enables measuring the similarity between a full color image and a simple black and white sketched query. We present efficient feature representation method namely rotation-invariant histograms of oriented gradients (Ri-HOG) for image retrieval. Most of the existing HOG techniques are computed on a dense grid of uniformly-spaced cells and use overlapping local contrast of rectangular blocks for normalization. However, we implement annular spatial bins type cells and apply radial gradient to attain gradient binning invariance for feature extraction. In this way, it significantly improves HOG in regard to rotation invariant ability and feature descripting accuracy. In experiments, the proposed method is evaluated on wang datasets. The experimental results demonstrate that the proposed method is much more effective than many existing image feature descriptors for sketch based image retrieval.
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Image retrieval, rotation, HOG.