• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.397-397
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• 2006

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.321-324
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• 2010

There have been lots of researches on a multi-core processor. The enhancement has been performed through parallelization method. Multi-core architecture in the mobile environment has emerged. But, there is a limit to a mobile CPU's performance. GP-GPU(General-Purpose computing on Graphics Processing Units) can improve performance without adding other dedicated hardware. This paper presents the implementation of Inverse Quantization, Inverse DCT and Color Space Conversion module in H.264/AVC decoder using Multi-Core GP-GPU for a mobile environments. The proposed architecture improves approximately 50% of performance when it use all the features.

• Journal of Biosystems Engineering
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• v.32 no.3
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• pp.160-165
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• 2007

This study was conducted to evaluate beef using a color machine vision system. The machine vision system has an advantage to measure larger area than a colorimeter and also could measure other quality factors like distribution of fats. However, the machine vision measurement is affected by system components. To measure the beef color with the machine vision system, the effect of color balancing control was tested and calibration model was developed. Neural network for color calibration which learned reference color patches showed a high correlation with colorimeter in L*a*b* coordinates and had an adaptability at various measurement environments. The trained network showed a very high correlation with the colorimeter when measuring beef color.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.455-461
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• 2002

Object-based image retrieval method is addressed. A new image segmentation algorithm and image comparing method between segmented objects are proposed. For image segmentation, color and texture features are extracted from each pixel in the image. These features we used as inputs into VQ (Vector Quantization) clustering method, which yields homogeneous objects in terns of color and texture. In this procedure, colors are quantized into a few dominant colors for simple representation and efficient retrieval. In retrieval case, two comparing schemes are proposed. Comparing between one query object and multi objects of a database image and comparing between multi query objects and multi objects of a database image are proposed. For fast retrieval, dominant object colors are key-indexed into database.

• Proceedings of the Korea Contents Association Conference
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• 2005.05a
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• pp.480-483
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• 2005

This study has proposed a method of content-based image retrieval in order to overcome disadvantages of color histogram. The existing histogram method has a weak point that reduces accuracy because of quantization error, and more. In order to solve this, we convert color information to HSV and quantize Hue factor being net color information and calculate histogram and then use this for retrieval feature that is robust in brightness, movement, and rotation. As a result of experimenting, the method proposed has showed better precision than the existing method.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.581-584
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• 2002

In this study, an algorithm for dithering true color image to 8-bit indexded color image using Artificial Neural Network was proposed. An adaptive vector quantization algorithm based on Artificial neural network was proposed for dithering color images. To evaluate the proposed algorithm, Mean Square Error(MSE) and quality between original image and dithered image was compared to those of other algorithm. As a results, MSE of proposed algorithm was lower than that of other algorithm used in commercial application and quality of dithered image was also highly improved.

• Journal of information and communication convergence engineering
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• v.16 no.4
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• pp.258-263
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• 2018

Color Doppler sonography is a useful tool for examining blood flow and related indices. However, it should be done by well-trained operator, that is, operator subjectivity exists. In this paper, we propose an automatic blood flow area extraction method from brachial artery that would be an essential building block of computer aided color Doppler analyzer. Specifically, our concern is to examine hypertension suspicious (prehypertension) patients who might develop their symptoms to established hypertension in the future. The proposed method uses fuzzy C-means clustering as quantization engine with careful seeding of the number of clusters from histogram analysis. The experiment verifies that the proposed method is feasible in that the successful extraction rates are 96% (successful in 48 out of 50 test cases) and demonstrated better performance than K-means based method in specificity and sensitivity analysis but the proposed method should be further refined as the retrospective analysis pointed out.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.473-481
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• 2005

In this paper, we propose an image segmentation method preserving object's boundaries by using the number of quantized colors and merging regions using adaptive threshold values. First of all, the proposed method quantizes an original image by a vector quantization and the number of quantized colors is determined differently using PSNR each image. We obtain initial regions from the quantized image, merge initial regions in CIE Lab color space and RGB color space step by step and segment the image into semantic regions. In each merging step, we use color distance between adjacent regions as similarity-measure. Threshold values for region-merging are determined adaptively according to the global mean of the color difference between the original image and its split-regions and the mean of those variations. Also, if the segmented image of RGB color space doesn't split into semantic objects, we merge the image again in the CIE Lab color space as post-processing. Whether the post-processing is done is determined by using the color distance between initial regions of the image and the segmented image of RGB color space. Experiment results show that the proposed method splits an original image into main objects and boundaries of the segmented image are preserved. Also, the proposed method provides better results for objective measure than the conventional method.

• Journal of Broadcast Engineering
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• v.17 no.4
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• pp.670-675
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• 2012

If the region of interest (ROI) is set within the picture of image and video and the high quality is provided in ROI compared to Non ROI, then overall subjective picture quality can be increased. ROI extracted by the color camera only increases the calculation complexity and reduces the extraction accuracy. In this paper, we use depth camera to set the ROI and calculate the object distance from camera, then propose a method that the different picture quality is controlled by depending on the distance of an object. That is, we apply a high quantization step size to the far object, but relatively a low quantization step size to the close object, so better picture quality can be provided. Simulation results show that applying the differential quantization step size to the distance of objects by the proposed method can improve the subjective picture quality.

• 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.