Convenient Clothing Pattern and Colour Recognition for People with Vision Impairment

Abstract

The objective of this paper is to design and
implement a prototype which is capable of recognizing
clothing patterns in four categories
(plaid,plain,irregular,striped) and identifies 12 colors.
Choosing clothes with complex patterns and colors is a
challenging task for visually impaired people. We have
developed a camera-based prototype system that has
an integrated camera, a microphone, a computer, and a
Bluetooth earpiece for audio description of clothing patterns
and colors. The clothing patterns and colors are described to
blind users orally. This system can be controlled by speech
input through microphone. To recognize clothing patterns, we
propose a novel Radon Signature descriptor and a schema to
extract statistical properties from wavelet sub-bands to
capture global features of clothing patterns. To evaluate the
effectiveness of the proposed approach, we used the CCNY
Clothing Pattern dataset. Our approach achieves 90%
recognition accuracy which significantly outperforms the
state-of-the-art texture analysis methods on clothing pattern
recognition.