Optical pattern recognition based on color vision models

Abstract

A channel transformation based on opponent-color theory of the color vision models is applied to optical pattern recognition so that the conventional red, green, and blue (RGB) channels are transformed into bright -dark, red -green, and yellow -blue (ATD) channels. Matched f iltering and correlation are performed over the new components of the target and the scene in the ATD system. The proposed transformation allows us to reduce the number of channels commonly used in color pattern recognition, passing from the three RGB channels to the two red -green and yellow -blue opponent-color channels. © 1995 Optical Society of AmericaThe introduction of color information in pattern recognition is especially useful when the contours and the intensity distribution do not provide enough information to permit the discrimination of images. The most extensive way to incorporate color into pattern recognition is through a trichromatic decomposition of the image into red, green, and blue (RGB) components that are independently analyzed. The RGB multichannel decomposition has been associated with matched filtering and optical correlation techniques for the performance of optical color pattern recognition. One of the methods used for the RGB decomposition is the illumination of a color transparency containing the target by three monochromatic wavelengths separately. 1,2The three wavelengths, belonging to the red, green, and blue regions, must be distributed in the visible spectrum. For the illumination of the optical correlator it has been proposed that the same wavelengths be used for the generation of the filters 2 or that a white-light source combined with a grating in the scene plane be used. 3Another method used for RGB decomposition is the acquisition and digitization of the image by a color camera. In this case the channels are defined by the response of the camera in a wide bandwidth. The RGB components of the scene are displayed in the correlator either on an achromatic spatial light modulator 3 or on a color spatial light modulator. 4 This method permits digital preprocessing of the acquired image before it is displayed.Different problems in polychromatic pattern recognition have been studied in Refs. 1-6. The most common problem is the recognition of a given object, taking into account both the shape and the color distribution. 1 -4 Other problems are the recognition of a given shape regardless of the color distribution of the object and the identif ication of the color of the diverse zones that compose the object. 5,6 Millán et al. 5 proposed a recognition strategy that involves the signals used to generate the matched filters and the decision criteria applied to the RGB multichannel correlation results. Yamaba and Miyake 6 proposed a transformation of the RGB components provided by the camera that considers the Hurvich-Jameson color vision model 7 with some modifications. Their recognition system is based on the projected weight values obtained from a learning process by a neural board.Color human vision models ba...

Digital color correlation for the recognition of Vibrio cholerae 01 in laboratory and environmental samples

“…The differences between our algorithm and those proposed by other authors (Millán et al 1989(Millán et al , 1991(Millán et al , 1992(Millán et al , 1995 depend on the monochromatic components of a polychromatic object in RGB channels. If any object, like fluorescent V. cholerae 01 is stained of green, and it exclusively has information in one channel the recognition must be done with the algorithm proposed in this work.…”

“…The algorithm presented here is different from the one used by other authors (Millán et al 1989(Millán et al , 1991(Millán et al , 1992(Millán et al , 1995 which proposed to recognize objects through the logic or arithmetic sum of results in the RGB channels. In other words, they considered a correct identification when the maximum correlation peaks appeared simultaneously in the three channels and a correct discrimination when it did not occur.…”

“…Combining color information with shape has previously resulted in a high level of target recognition (Bradiqué, 1987, Millán et al 1989, 1991, 1992, Ferreira et al 1992, Millán et al 1995. Since the color observed depends on the wavelength of illumination, a polychromatic object can be decomposed using monochromatic channels.…”

<title>3D filter design for color pattern recognition</title>

“…The information of each channel is taken into account to take the final decision on the recognition. Some component transformations have been proposed, based either on the use of color vision models 6 , or on the use of the theory of optimal filter applied to multi-spectral images 7 .…”

Color pattern recognition with circular component whitening

“…Another fruitful approach involves preprocessing of the RGB components on the basis of human perception. 7 It is known that the RGB components of the original color image are strongly correlated with one another. We propose to perform component transformation by carrying out whitening operation along the color axis.…”