Hyun Jin Lee, Eun Jin Kim, Yil Byung Lee

The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 6, No. 11, pp. 3165-3177, Nov. 1999
10.3745/KIPSTE.1999.6.11.3165,   PDF Download:

Abstract

With the recent outstanding advance in computer software and hardware, a number of researches to enhance the manufacturing speed and the process accuracy has been undertaken in many fields of textile industry. Frequently issued problems of automatic recognition of textile wrinkles in a grey scale image are as follows. First, changes in grey level intensity of wrinkles are so minute. Second, as both colors and patterns in a grey scale image appear in grey level intensity, it is difficult to sort out the wrinkle information only. Third, it is also difficult to distinguish grey intensity changed by wrinkles from those by uneven illumination. This paper suggests a method of automatic recognition of textile wrinkles that can solve above problems concerned with wrinkles, which can be raised in a manufacturing process as one of errors. In this paper, we first make the outline of wrinkles distinctly, apply the block matching algorithm used in motion estimation, and then estimate block locations of target images corresponding to blocks of standard images with the assumption that wrinkles are kind of textile distortions caused by directional forces. We plot a "wrinkle map" considering distances between wrinkles as depths of wrinkles. But because mismatch can occur by different illumination intensity and changes in tensions and directions of the force, there are also undesirable patterns in the map. Post processing is needed to filter them out and get wrinkles information only. We use average grey level intensity of wrinkle map to recognize wrinkles. When it comes to textile with colors and patterns, previous researches on wrinkles in grey scale image hasn't been successful. But we make it possible by considering wrinkles as distortion.

Statistics
Cite this article