• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.339-340
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• 2007

Face detection plays an important role in HCI and face recognition. In this paper, we propose a rotation-invariant real-time face detection algorithm for color images in complex background. It consists of four processing step: (1) motion detection, (2) skin color region filler, (3) Eyemap detector for rotated face, and (4) Adaboost face classifier. This system has been tested in in-door environments, such as office and achieves over 95% detection rate.

• KSCI Review
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• v.15 no.1
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• pp.185-190
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• 2007

An image retrieval system is a piece of software that searches identical or similar images based on various image-specific features. This paper proposes a trademark image retrieval system that uses image colors and forms. In the proposed system, input images are segmented into several other regions, and color distribution histograms for different regions are extracted for use as color information. The proposed system uses form information through the preprocessing process such as boundary surface extraction, centroid extraction, angular sampling and, and through calculating the sums of the distances between the centroid and the boundary surfaces, standard deviations, and the ratios between long and short axes. Like this, the color and form information extracted is used to perform retrieval through measuring similarity.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.294-298
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• 2000

As the LED or LCD technology has been developed, if we use LED or LCD pannel, more wide color range coluld be obtained as CRT monitor. Specially, full color LED display is developed by high brightness blue LED. It can be applicable to display pannel with a long-life, wide visible angle and high brightness. A display pannel shows the images of CRT monitor performed by the main computer. Graphic application in the main computer is therefore more important in the market. Conventional 3D STUDIO, one of graphic softwares, has difficulties in manipulating and understanding the specific terminology so that one may need more time to learn it. We, therefore, developed graphic application which can recycle the conventional 3D images by creating or editing the image easily.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.211-227
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• 2011

Content Based Image Retrieval (CBIR) is an approach for retrieving similar images from an image database based on automatically-derived image features. The quality of a retrieval system depends on the features used to describe image content. In this paper, we propose an image clustering system that takes a database of images as input and clusters them using k-means clustering algorithm taking into consideration color, texture and shape features. Experimental results show that the combination of the three features brings about higher values of accuracy and precision.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1271-1278
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• 2018

The NDT using ultrasonic is largely divided into A-Scan and C-Scan methods. Since A-Scan method is subject to subjective judgement by trained personnel, C-Scan method has been introduced, which presents the weld area in two dimensions by placing the transducers two dimensionally used in the A-Scan method. Therefore, it is necessary to develop equipment that can provide weld quality without the help of a welding expert and the presentation of effective C-Scan images. Thus, in this paper, the algorithms that express a low resolution 2-dimensional gray image formed by C-Scan method as a high-resolution color C-Scan image and automatically determine the weld quality from the generated C-Scan color image. The high resolution color C-Scan images proposed in this paper allow the exact shape of the weld point to be expressed, and an objective algorithm to use this image to automatically determine weld quality.

• Annual Conference of KIPS
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• 2013.05a
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• pp.215-218
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• 2013

In this paper, we proposed a method for enhancement of color images with sky regions. The input image is converted into HSV space and then sky and non-sky regions are separated. For sky region, saturation enhancement is performed for each pixel based on the enhancement factor calculated from the average saturation of its local neighborhood. On the other hand, for the non-sky region, the enhancement is applied only on the luminance value (V) component of the HSV color image, which is performed in two steps. The luminance enhancement, which is also called as dynamic range compression, is carried out using nonlinear transfer function. Again, each pixel is further enhanced for the adjustment of the image contrast depending upon the center pixel and its neighborhood pixel values. At last, the original H and V component image and enhanced S component image for the sky region, and original H and S component image and enhanced V component image for the non-sky region are converted back to RGB image.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1291-1294
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• 2003

This paper presents an approach to extract license plates from parking regulation images which is captured in various photographing direction and complex background. first, we search each row at regular intervals starting from the bottom of a license-plate image, and we set up a rough region for a certain zone in which the sign of intensity vector changes frequently enough and color of license plate is detected enough, assuming it as a candidate location of a license plate. And then, we extract an elaborate area of a license plate by horizontally and vertically projecting vertical edges. Here, tar types of the private and the public, are easily classified according to the color of extracted plates. To evaluate proposed method, we used 200 actual regulation images. As a result, the proposed method showed extraction rate of 96%, which is 9% higher than the previous method using only intensity vector.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.9
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• pp.1276-1282
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• 2013

This paper presents a demosaicking method based on high-order interpolation with parameters. Demosaicking is an essential process in capturing color images through a single sensor-array. Thus, a lot of methods including the Hamilton-Adams(HA) method has been studied in this literature. However, the image quality depends on various factors such as contrast and correlation in color space; existing algorithms depend on test images in use. Consequently, a new test image set was suggested to develop demosaicking algorithms properly. According to previous studies, the HA method shows high performances with the new test data set. In this paper, we improve the HA method using high-order interpolation with parameters. Also, we provide an analysis and formulations for the proposed method. To evaluate our method, we compare our method with the existing methods both objectively and subjectively. The experimental results indicate that the proposed method is superior to the existing methods.

• International Journal of Contents
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• v.14 no.3
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• pp.1-6
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• 2018

For 3D display applications, auto-stereoscopic display methods that can provide 3D images without glasses have been actively developed. This paper is concerned with developing a display system for elemental images of real space using integral imaging. Unlike the conventional method, which reduces a color image to the level as much as a generated depth image does, we have minimized original color image data loss by generating an enlarged depth image with interpolation methods. Our method was efficiently implemented by applying a GPU parallel processing technique with OpenCL to rapidly generate a large amount of elemental image data. We also obtained experimental results for displaying higher quality integral imaging rather than one generated by previous methods.

• Journal of Integrative Natural Science
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• v.13 no.2
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• pp.83-86
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• 2020

In In this study, technique has been suggested according to the calculation of thresholds of histogram based on overlap areas for reducing noise while analyzing the functions of them. Suggested algorithm is to convert histogram extracted from color images to gray level and select overlap areas from extracted histogram. In addition, feature table is configured after extracting histogram in the relevant overlap area while comparing and retrieving for query and database video images by using this feature table. Suggested retrieval system has been confirmed to be more outstanding with retrieval function in video images with more noises than the system that only used color histogram.