Abstract
In this paper, we present Fuzzy Counter Propagation Network (FCPN) for Sketch-Based Image Retrieval (SBIR) with collection of freehand sketches; trademark and clip art, etc., using feature descriptors. FCPN is combination of Counter Propagation Network (CPN) and Fuzzy Learning (FL). We use features descriptor like Histogram of Gradient (HOG) for freehand sketches/images and these features are used to the training of FCPN. Flicker dataset containing 33 different shape categories, is used for training and testing. Different similarity measure functions are discussed and used similarity between query by nonexpert sketchers and database. We compare proposed FCPN method with other existing Feed-forward Networks (FFN) and Pattern Recognition Network (PRN). Experimental results show that FCPN methods outperform over networks.
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Agrawal, S., Singh, R.K., Singh, U.P. (2019). Fuzzy Counter Propagation Network for Freehand Sketches-Based Image Retrieval. In: Ray, K., Sharma, T., Rawat, S., Saini, R., Bandyopadhyay, A. (eds) Soft Computing: Theories and Applications. Advances in Intelligent Systems and Computing, vol 742. Springer, Singapore. https://doi.org/10.1007/978-981-13-0589-4_16
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DOI: https://doi.org/10.1007/978-981-13-0589-4_16
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