Automatic Choising Pattern Recognition Essay

Abstract—Choosing clothes with complicated patterns and colors is a challenging task for visually impaired people. Automatic clothing pattern recognition is also an ambitious research problem due to rotation, scaling, illumination, and especially large intraclass pattern variations. This approach is to design a prototype that will help to produce a real time product development for visually impaired people. Recognizing automatically clothing patterns and having different colors may their life better and improve their life quality. The designed prototype will cover most of the clothing pattern such as plaid, striped, pattern-less, and irregular. It also recognize 11 type of colors like red, orange, yellow, green, cyan, blue, purple, pink, black,

Choosing clothes with complex colors and patterns is a challenging task for blind or visually impaired people. They manage their task with the help of their family members, using plastic labels or different types of stitching pattern tags on the clothes, or by wearing clothes with a uniform color or without any patterns. Automatically recognizing clothing patterns and colors may better their life quality. Although many methods have been developed for texture matching and color sensing in the computer vision and image processing research, currently there is no instrument that can effectively supply matching choices for blind people. Algorithm can detect: 1) Colors of the clothes; 2) whether the clothes have pattern or have homogeneous color; 3) whether the colours match for a pair of images. Here, I introduce a prototype to help visually impaired people to recognize clothing patterns and colors. The system contains three major components: (1)existing images having different clothing patterns, (2)clothing pattern recognition and color identification by using a computer which can be a desktop, (3)Audio outputs or a text message to provide recognition results of clothing patterns and colors. The image pair is captured by a camera which is connected to a computer. The system focus on these kind of fields where such as pattern

Liu et al. fabricated an attire suggestion framework for particular events (e.g., wedding or dating). Hidayati et al. proposed a technique for type characterization of upper-wear garments. The two frameworks are both composed without thinking about key components for blind people. Yuan et al. built up a framework to help blind individuals to coordinate garments from a couple of cloth pictures. This framework can furnish a client with the data about regardless of whether the garments examples and hues coordinate. However this framework can't naturally perceive clothing designs. Surface gives basic data to many picture order undertakings including cloth design recognition. Some early inquiry on surface acknowledgment concentrated on the examination of worldwide two-dimensional (2-D) picture changes incorporating into plane turn and scaling. Because of the absence of invariance to general geometric changes, these methodologies can't adequately speak to surface pictures with expansive 3-D changes, for example, perspective change and non inflexible surface misshapening. Multi fractal investigation has accomplished great strength to 3-D distortions. Texture representation is an advantage from the invariance of fractal measurements to geometric changes. For instance,