• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.106-109
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• 2003

This paper presents a hue preserving gamut mapping algorithm for color monitor and printer. The gamuts of monitor and printer are set by the profile of color reproduction media, specified by ICC(International Color Consortium) and provided by vendors, then those gamuts are represented on the CIE xy color space. In case that the color of monitor are located on out-of-gamut of printer, these are clipped on the point of gamut boundary of printer towards a reference white point. On the other hand, colors are in-gamut of printer are unchanged. An image generated by the algorithm keeps a ratio of each pixel of original image. Advantages of the algorithm are easy to implement and fast processing time than other algorithms which involve hue preserving especially in CIELAB color space.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.101-110
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• 1996

Color image quantization is a process of selecting a set of colors to display an image with some representative colors without noticeable perceived difference. It is very important in many applications to display a true color image in a low cost color monitor or printer. the basic problem is how to display 224 colors with 256 or less colors, called color palette. In this paper, we propose an algorithm to design the 256 or less size color palette by using spatial maskin geffect of HVS and subjective distortion measure weighted by color palette by using spatial masking effect of HVS and subjective distortion measure weighted by color activity in 4*4 local region in any color image. The proposed algorithm consists of octal prequantization and subdivision quantization processing step using the distortion measure and modified Otsu's between class variance maximization method. The experimental results show that the proposed algorithm has higher visual quality and needs less consuming time than conventional algorithms.

• Korean Journal of Remote Sensing
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• v.9 no.1
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• pp.37-49
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• 1993

In this research, the WEF AX and APT(Automatic Picture Transmission) data receiving and image processing software using PC/AT called WADIPS(WEFAX and APT Data Integrated Processing System) Software has been developed. The main functions of WADIPS software are follow : 1) Real time receiving and saving to hard disk of WEFAX and APT data 2) B/W(Black and White) and false color display 3) Image enhancement using histogram stretch and color control 4) 2-4 times zooming 5) Hard copy of data using dithering and patterning 6) Animation 7) File management 8) On line help. WADIPS can be used in the offices or persons need real time meteorological information and education offices to teach the image processing technique and general characteristics of meteorological satellites.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.170-177
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• 2000

Sorting cut roses according to quality is very essential to increase the value of the product. Many factors are involved in determining the grade of cut roses: length, thickness, and straightness of stem, color and maturity of bud, and extra. Among these factors, the stem straightness and bud maturity are considered to be difficult to set proper classification criteria. In this study, a prototype machine and an analysis procedure were developed to grade cut roses according to stem straightness and bud maturity by utilizing color image processing and neural network. The test results indicated 15.8% classification error for stem straightness and 10.0% for bud maturity.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.1
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• pp.8-16
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• 2012

An image obtained from a low light environment results in a low-exposure problem caused by non-ideal camera settings, i.e. aperture size and shutter speed. Of particular note, the multiple color-filter aperture (MCA) system inherently suffers from low-exposure problems and performance degradation in its image classification and registration processes due to its finite size of the apertures. In this context, this paper presents a novel method for the color enhancement of low-exposure images and its application to color shift model-based MCA system for image refocusing. Although various histogram equalization (HE) approaches have been proposed, they tend to distort the color information of the processed image due to the range limits of the histogram. The proposed color enhancement algorithm enhances the global brightness by analyzing the basic cause of the low-exposure phenomenon, and then compensates for the contrast degradation artifacts by using an adaptive histogram specification. We also apply the proposed algorithm to the preprocessing step of the refocusing technique in the MCA system to enhance the color image. The experimental results confirm that the proposed method can enhance the contrast of any low-exposure color image acquired by a conventional camera, and is suitable for commercial low-cost, high-quality imaging devices, such as consumer-grade camcorders, real-time 3D reconstruction systems, digital, and computational cameras.

• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.9-14
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• 2015

In this paper, we present an color quantization method by complementing the disadvantage of K-means color quantization that is one of the well-known color quantization. We named the proposed method "octree-means" color quantization. K-means color quantization does not use all of the clusters because it initializes the centroid of clusters with random value. The proposed method complements this disadvantage by using the octree color quantization which is fast and uses the distribution of colors in image. We compare the proposed method to six well-known color quantization methods on ten test images to evaluate the performance. The experimental results show 68.29 percent of mean square error(MSE) and processing time increased by 14.34 percent compared with K-means color quantization. Therefore, the proposed method improved the K-means color quantization and perform an effective color quantization.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.63-65
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• 2005

In this study, the automatic face tracking algorithm is proposed by using the color and edge information of a color image. To reduce the effects of variations in the illumination conditions, an acquired CCD color image is first transformed into YCbCr color coordinates, and subsequently the morphological image processing operations, and the elliptical geometric measures are applied to extract the refined facial area.

• Annual Conference of KIPS
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• 2010.11a
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• pp.705-708
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• 2010

An eigen color co-occurrence approach is proposed that exploits the correlation between color channels to identify the degree of image similarity. This method is based on traditional co-occurrence matrix method and histogram equalization. On the purpose of feature extraction, eigen color co-occurrence matrices are computed for extracting the statistical relationships embedded in color images by applying Principal Component Analysis (PCA) on a set of color co-occurrence matrices, which are computed on the histogram equalized images. That eigen space is created with a set of orthogonal axes to gain the essential structures of color co-occurrence matrices, which is used to identify the degree of similarity to classify an input image to be tested for various purposes. In this paper RGB, Gaussian color space are compared with grayscale image in terms of PCA eigen features embedded in histogram equalized co-occurrence features. The experimental results are presented.

• Annual Conference of KIPS
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• 2000.10b
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• pp.859-862
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• 2000

본 논문에서는 기존의 TV 시스템에서 사용하는 영상신호의 encoding/decoding 방법과 새롭게 제안되는 constant luminance encoding/decoding 방법을 컴퓨터로 구현하고, 기존의 방법과 제안된 방법으로 재생된 영상의 칼라 정보의 차이에 대한 데이터를 제시한다. 또한 디지털 방송에 적합한 encoding/decoding 시스템의 선택에 대한 고찰도 포함한다.

• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.319-326
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• 2004

In this paper, we propose color image segmentation by region merging method preserving the boundary of an object. The proposed method selects initial region by using quantized image's index map after vector quantizing an original image. After then, we merge regions by applying boundary restricted factor in order to consider the boundary of an object in HSI color space. Also we merge the regions in RGB color space for non-processed regions in HSI color space. And we reduce processing time by decreasing iterative process in region merging algorithm. Experimental results have demonstrated the superiority in region's segmentation results and processing time for various images.