• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1996.06a
• /
• pp.181-185
• /
• 1996

Color image is largely corrupted by various ambient illumination. However, human perceives always white color as white under any illumination because of a characteristic of human vision, called color constancy. In the conventional algorithm which applied the constancy effect, after the RGB color space is transformed to the IHS(Intensity, Hue, and Saturation) color space, then the hue is preserved and the intensity or the saturation is properly enhanced. Then the enhanced IHS color is reversely transformed to the RGB color space. In this process, the color distortion is included due to the color gamut error. But in the proposed algorithm, there is not transformation. In that, the RGB color is considered as 3 dimensional color vector and we assume that white color is the natural daylight. As the color vector of the illumination can be calculated as the average vector of R, G, and B image, we can achieve the constancy effect by simply rotating the illumination vector to the white color vector. The simulation results show the efficiency of the vector rotating process for color image enhancement.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.6 no.2
• /
• pp.116-120
• /
• 2006

This paper discusses an approach for detecting a new edge in color images. The color image is to be represented by a vector field, and the color image edges are detected as differences in the local vector statistics. This method is based on the calculation for the vector angle between two adjacent pixels. Unlike Euclidean distance in RGB space, the vector angle distinguishes the differences in chromaticity, independent of luminance or intensity. The proposed approach can easily accommodate concepts, such as variable template edge detection, as well as the latest developments in vector order statistics for color image processing. In this paper, it is used not a conventional fixed template operator but a variable template operator The variable template is implemented and experimental results for digital color images are included.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.5
• /
• pp.77-85
• /
• 2004

This paper proposes a multi-level vector error diffusion method using 64 primary colors to improve color impulse artifact in bright region. Vector error diffusion method causes color impulse artifact in bright region because we only use the Euclidean distance measure in quantization process. In order to reduce this artifact, the proposed method divides input color into chromatic color and achromatic color according to chroma value. In the case of chromatic color, input color is classified into bright region, middle bright region, and dark region according to lightness value. N candidate primary color is organized using lightness difference between input vector and 60 chromatic primary color vector in the case of bright region. Then, primary color with minimum vector norm between input vector and N candidate primary color in addition to 4 achromatic primary colors is selected as output color. As a result of experiments, the proposed method showed visually pleasing halftone output.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.3
• /
• pp.111-120
• /
• 2004

This paper proposes a vector error diffusion method for smear artifact reduction in the boundary region. This artifact mainly results from a large accumulation of quantization errors. In particular, color bands with a smear artifact, the width of a few pixels appear along the edges. Accordingly, to reduce this artifact, the proposed halftoning process excludes the large accumulated Quantization error by comparing the vector norms and vector angles between the error-corrected vector and eight primary color patches. When the vector norm of the error corrected vector is larger than those of eight primary color patches, the quantization error vector is excluded from the quantization error distribution process. In addition, the quantization error is also excluded when the angle between eight primary color patches and error corrected vector is large. As a result, the proposed method enables a visually pleasing halftone pattern to be generated by all three color separations into account in a device- independent color space and reduces smear artifact in the boundary regions.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.6 s.44
• /
• pp.79-86
• /
• 2006

Classification technology is essential for fast retrieval in large multi-media database. This paper proposes a combining GA(Genetic Algorithm) and SVM(Support Vector Machine) model to fast retrieval. We used color and texture as feature vectors. We improved the retrieval accuracy by using proposed model which retrieves an optimal feature vector set in extracted feature vector sets. The first performance test was executed for the performance of color, texture and the feature vector combined with color and texture. The second performance test, was executed for performance of SVM and proposed algorithm. The results of the experiment, using the feature vector combined color and texture showed a good Performance than a single feature vector and the proposed algorithm using hybrid method also showed a good performance than SVM algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.5 s.305
• /
• pp.1-10
• /
• 2005

Content-based image retrieval systems are being actively investigated owing to their ability to retrieve images based on the actual visual content rather than by manually associated textual descriptions. In this paper, we propose a novel approach for image retrieval based on edge structural features using edge correlogram and color coherence vector. After color vector angle is applied in the pre-processing stage, an image is divided into two image parts (high frequency image and low frequency image). In low frequency image, the global color distribution of smooth pixels is extracted by color coherence vector, thereby incorporating spatial information into the proposed color descriptor. Meanwhile, in high frequency image, the distribution of the gray pairs at an edge is extracted by edge correlogram. Since the proposed algorithm includes the spatial and edge information between colors, it can robustly reduce the effect of the significant change in appearance and shape in image analysis. The proposed method provides a simple and flexible description for the image with complex scene in terms of structural features of the image contents. Experimental evidence suggests that our algorithm outperforms the recently histogram refinement methods for image indexing and retrieval. To index the multidimensional feature vectors, we use R*-tree structure.

• Journal of the Institute of Convergence Signal Processing
• /
• v.8 no.4
• /
• pp.293-296
• /
• 2007

In this paper, we propose the systolic array architecture for the vector median filter. In the color image processing, the vector signal (i.e. the color) consists of three elements, red, green and blue. The vector median filter is very effective to utilize the correlation among red, green and blue elements. The computational complexity of the proposed architecture for computing the vector median of N vector signals is (N+2) clock periods compared to the (3N+1) clock periods in the previous method. In addition to, the input vector signals can be loaded in serial in the proposed architecture. In the previous method, N input vector signals should be loaded to the vector median filter in parallel at the first clock. The proposed architecture is implemented with FPGA.

• Journal of the Korean Graphic Arts Communication Society
• /
• v.18 no.2
• /
• pp.1-12
• /
• 2000

This paper proposes a new algorithm classifing same hues in order toe estimate the spectral reflectance of object from 3 band color image information. To estimate the spectral reflectance of object, the conventional estimation methods are required of 5 or 9 band digital color values. The 5 or 9 band image acquisition systems are required of 5 or 3 times same work for color image acquisition process. To solve the above problems, we propose a new method that can be estimated spectra reflectance estimation of object. The proposed method is to classify same hues corresponding a color stimulus, by using hue angle and chroma vector of a color stimulus. The classified same hues are used as the population corresponding a color stimulus. The range of same hue is estimated by the cumulative proportional ration according to the number of basis function.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.37 no.5
• /
• pp.76-83
• /
• 2000

This paper proposes a new color halftorning method using color correction by vector error diffusion to reduce color difference, necessarily appears on cross-media color reproduction In order to predict output colors on each device, a neural system IS applied and mean prediction errors in device characterization for monitor and printer are defined to calculate the thresholds for color correction Thus, color difference between monitor and printer is compared per each pixel If color difference is larger than the predetermined mean prediction errors, the halftoned dots to the current pixel are rearranged by vector error diffusion The proposed method can reduce the smear artifact by selective vector error diffusion and decrease color difference on cross- media color reproduction by color correction.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.12
• /
• pp.3718-3726
• /
• 1999

Color image is more effective than gray one in human visual perception. Therefore, color image processing becomes important area. Color images are often corrupted by noises due to the input sensor, channel transmission errors and so on. Some filtering techniques such as vector median, mean filter, and vector $\alpha-trimmed$ mean filter have been used for color noise removal. Among them, vector $\alpha-trimmed$ mean filter gave the best performance in the mixed color noise. But, there are edge shift and blurring effect because vector $\alpha-trimmed$ mean filter is uniformly processed across the image. So, we proposed a conditional fuzzy cluster filter to improve this problems. Simulation results showed that the proposed scheme improves the NCD measure and visual quality over the conventional vector $\alpha-trimmed$ mean filter in the mixed color noise.