Author :
Pei, Soo-Chang ; Ding, Jian-Jiun ; Chang, Jahan
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Abstract :
It is popular to use the conventional correlation for pattern recognition. But when using the conventional correlation, the pattern should be the gray-level pattern. In this paper, we discuss how to use discrete quaternion correlation (DQCR) for the application of color pattern recognition. With the algorithm introduced here, we can detect the objects that have the same shape, color, and brightness as the reference pattern. Besides, we can also detect (a) the objects with the same shape, color, but different brightness, (b) the objects with the same shape, brightness, but different color, and (c) the objects just have the same shape as the reference. Our algorithm can classify the objects into 5 classes due to whether their shape, brightness, and color match those of the reference pattern. Besides, with our algorithm, the difference of the brightness and color can also be calculated at the same time
Keywords :
correlation methods; image classification; image colour analysis; DQCR; brightness; classification; color pattern recognition; conventional correlation; discrete quaternion correlation; gray-level pattern; shape; Brightness; Flexible printed circuits; Image analysis; Image color analysis; Object detection; Pattern matching; Pattern recognition; Pixel; Quaternions; Shape;
