Maeng-Sub Cho

Device calibration of a color image scanner digitizing system by using neural networks

In the color image analysis, color images can be captured through color video cameras or color image scanners. The calibration of a color image capturing device is required as digitizing systems spectral sensibilities are not always identical to the human color matching functions. Calibration can be abstracted as a modeling problem from a device dependent color space to a device independent and uniform color space. In this paper, a neural network model is proposed for converting a device-dependent color space to a device-independent color space. Statistical, optimization, and genetic algorithm approaches are compared with the neural network method to find the best model with the smallest resultant /spl Delta/Ea*b*. Conclusions are drawn with experimental results.

Linear programming method for computing the gamut of object color solid

Recently there has been great interest in establishing the color gamut of solid colors or the optimum colors. The optimum colors are widely used for quantifying the quality of light sources and evaluating reproduction devices. An enumeration method was developed by Martinez-Verdu et al. [J. Opt. Soc. Am. A 24, 1501 (2007)] for finding optimum colors. However, it was found that the method is too time-costly. In this paper, a linear programming approach is proposed. The proposed method is simple and faster and has the advantage of keeping the characteristics of the true boundary. Comparison of the present method with the method of Martinez-Verdu et al. is also given.

Fuzzy inference and logical level methods for binary graphic/character image extraction

Thresholding is one of the most important approaches to image segmentation. It has been widely used to characterize many images containing some objects of reasonably uniform brightness against a background of differing brightness. Typical examples include handwritten/typewritten text and microscope bio-medical samples. Even though it can be applied to the image processing widely, there is no robust thresholding technique to circumvent noisy image. In this study, firstly, the published character/graphic image extraction techniques were reviewed and investigated and new thresholding technique such as fuzzy inference and modified logical level are proposed. In fuzzy inference technique, new methods of fuzzification, fuzzy rule, and defuzzification are introduced for lower error and high speed image binarization.

Learning rate updating schemes of unsupervised learning

This paper first presents the improved convergence method using adjust learning rate (/spl alpha/) and clustering analysis in Kohonens network. New learning rate method which adopts hyperexponential function to reduce the influence of order presented of input patterns improves the convergence time in training. We also propose the new error measuring method using Hamming distance between patterns of each class and cluster center, Secondly, new strategy to speed up training the GLVQ is also proposed. Instead of using learning update scheme by Pal et al. (1993), we introduce adaptive learning rate updating strategy. Though Pal et al.s approach needs a priori information, approach proposed works without external parameters, and convergence time is reduced compared with Pal et al.s.

Colour image difference analysis: quantitative versus qualitative methods

This paper describes investigation of statistical correlation between the results of two image colour difference criteria: qualitative and quantitative. The aim is that, provided there is consistently high correlation between the results of the different methods, the quantitative method, which is relatively more convenient, could be used instead of the much more laborious qualitative psychophysical method.

Adaptive hierarchical stereo matching using object segmentation and window warping

In this paper, we propose an adaptive stereo matching algorithm to encompass stereo matching problems in projective distortion region. Since the projective distortion region can not be estimated in terms of fixed-size block matching algorithm, we tried to use adaptive window warping method in hierarchical matching process to compensate the perspective distortions. In addition, probability theory was adopted to encompass uncertainty of disparity of points over the window in this study. The proposed stereo matching algorithm has been tested on both disparity map and 3D model view. The experimental results show that remarkable improvement is obtained in the projective distortion region.

A simultaneous gamut compression with extended line of cusps

In many industrial areas, exact color reproduction is needed as an aspect of the appearance of color on cross media. The paper introduces the new gamut mapping algorithm which uses the extended line of two cusps. The point in the original gamut has been mapped in the reproduction gamut in L*-C* space, and each coordinate is mapped simultaneously. The experiment showed that the proposed algorithm acquired a higher chroma (C*) than the previous algorithm and the use of the whole range of gamut.

Colorimetric characterization for digital camera by using multiple regression

Digital cameras provide a very useful way of capturing images for use in image processing and color communications. Many of techniques have developed to obtain high-quality color digital images. But the RGB signals generated by digital cameras are device dependent and not colorimetric. We have extracted the device independent characteristics of digital cameras and made transfer matrices to transform the RGB color signals into the CIE XYZ tristimulus values. The least square fitting technique was used to derive the coefficients of 3/spl times/m polynomial transfer matrices. We have investigated the degree of the polynomial and the number of color samples which produce the best result. The parameters affecting the characterization were also described.

Characterizing the desktop color printer with polynomial regression

In many application areas, the printer has played a key role of reproducing the digital color images. According to the characteristics of output devices, the uncorrected distortion has arisen in the reproduced color. This paper proposed the color correction based on polynomial regressions that represented the characteristics of the desktop color printer. In addition, the proper number of sample used in obtaining the regression equation was investigated. The experiments showed the possibilities of the proposed methods by comparing the /spl Delta/Eab value between the original color and the corresponding reproduced color.

Development of a consistent color reproduction software for digital cinema

As presented in this paper, we described the development of a consistent color reproduction software. The consistent color reproduction software was developed for the digital cinema production chain which covers shooting, post-production and screening. The consistent color reproduction software can produce digital cinema images which have minimized average color differences between display devices.