Extended Noise Adaptive Binary Pattern for Garments Pattern Classification (original) (raw)

2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2), 2019

Abstract

Garments and fashion industries play a vital role in our economy. The automatic classification and recognition of garments design class may help in development of fashion industry. For this purpose, different feature descriptors have been proposed to extract discriminative information from the garments texture images. In this paper we proposed a new descriptor namely Extended Noise Adaptive Binary Pattern (ENABP). To evaluate this descriptor, we use two different publicly available datasets (Fashion and Clothing attribute dataset). The experimental result shows that ENABP produces better accuracy than NABP and other existing descriptor.

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