Improved local descriptor (ILD): a novel fusion method in face recognition.

Literature suggests that by fusing multiple features there is immense improvement in the recognition rates as compared to the recognition rates of single descriptor. This motivate researchers to develop more and more fused descriptors by joining multiple features. Inspiring from the literature work, the proposed work launch novel local descriptor so-called Improved Local Descriptor (ILD), by joining features of 4 local descriptors. These are LBP, ELBP, MBP and LPQ. LBP captures local details. ELBP capture robust features in horizontal and vertical directions (elliptically) by using 3 × 5 and 5 × 3 patches. MBP minimizes image noise by median comparison to all the pixels and LPQ quantize the frequency components for obtaining feature size. These essential merits of 4 descriptors are encapsulated in one framework in the form of histogram feature. PCA is used further for compression and SVMs and NN are used for classification. Results on ORL, GT and Faces94 confirms strength of ILD, which beats separately implemented descriptors and various benchmark methods. © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Citation

Shekhar Karanwal. Improved local descriptor (ILD): a novel fusion method in face recognition. International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management. 2023;15(4):1885-1894

PMID: 37256030

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