Title :
Classification of periodic patterns using Hough transform
Author :
Campos, Jesse ; Kasparis, Takis
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Central Florida, Orlando, FL, USA
Abstract :
Texture is an important characteristic in an image, and it is used to identify objects or regions of interest within an image. The problem of texture classification has been widely studied and most of the proposed techniques fall into two categories: statistical or structural. In this paper, a structural approach based on the Hough method for line detection is proposed for the description of periodic textures that consist of mostly straight lines. The features used for the classification procedure are based on the relative orientations and separations of lines. With the proper normalizations, classification is independent of geometrical transformations such as rotation, translation and/or scaling. This approach provides more unique features compared to other approaches. Experimental results with test patterns are presented
Keywords :
Hough transforms; geometry; image recognition; image texture; Hough transform; geometrical transformations; image texture classification; line detection; line separations; normalization; periodic pattern classification; relative line orientations; straight lines; structural approach; Image analysis; Image segmentation; Image texture; Image texture analysis; Inspection; Layout; Robot vision systems; Service robots; Surface texture; Testing;
Conference_Titel :
Southeastcon '94. Creative Technology Transfer - A Global Affair., Proceedings of the 1994 IEEE
Conference_Location :
Miami, FL
Print_ISBN :
0-7803-1797-1
DOI :
10.1109/SECON.1994.324337