Clothing Colour & Pattern Recognition for Visually Defective Persons using Grey Level Discrete Wavelet Transform Technique
Vishnuraj. P1, D. Vimal Kumar2

1Vishnuraj.P*, Research Scholar, Department of Computer Science Nehru Arts & Science College, Coimbatore, Tamil Nadu.
2D. Vimal Kumar, Associate Professor, Department of Computer Science Nehru Arts & Science College, Coimbatore, Tamil Nadu.
Manuscript received on April 21, 2020. | Revised Manuscript received on April 27, 2020. | Manuscript published on April 30, 2020. | PP: 2274-2278 | Volume-9 Issue-4, April 2020. | Retrieval Number: C5923029320/2020©BEIESP | DOI: 10.35940/ijeat.C5923.049420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: : collecting materials with different colours, patterns are complicated process for visually defective persons. Systematic materials pattern identification is also a denounce investigation highest different pattern deviations. In the study of living human-computer-interaction (HCI) implementation and apply of methods digitalized systems mainly focusing on the particular persons. This system mainly introduces the automatic study on “Blind & visually defective persons HCI and access to GUI produce a recent scenario imminent solution for visually defective persons and deliver together a new investigation. This Proposed system developed camera-captured on the real cloth identification garments patterns into under 4 diperception (plaid, stripped, pattern less, and 11 garments colours. The camera, a computer, a microphone, and of garments colours. Surrounded upon a pair of images. The garments colours are defined to authorizations. Present, managed by input speech m-phone. To recognize garments patterns, novel RSD and a wavelet sub bands to capture main features of garments patterns. To calculated effectiveness proposed accuracy, for apply various Garments Pattern dataset. Our approaches have 95-98% recognition accuracy which gathered output performs.
Keywords: Garments pattern identification, dependable cloth system, texture analyze, global and local features, visually defective persons.