• The KIPS Transactions:PartD
• /
• v.11D no.1
• /
• pp.23-30
• /
• 2004

In order to approximate the spatial query result size we partition the input rectangles into subsets and estimate the query result size based on the partitioned spatial area. In this paper we examine query result size estimation in skewed data. We examine the existing spatial partitioning techniques such as equi-area and equi-count partitioning, which are analogous to the equi-width and equi-height histograms used in relational databases, and examine the other partitioning techniques based on spatial indexing. In this paper we propose a new spatial partitioning technique based on the Hilbert space filling curve. We present a detailed experimental evaluation comparing the proposed technique and the existing techniques using synthetic as well as real-life datasets. The experiments showed that the proposed partitioning technique based on the Hilbert space filling curve achieves better query result size estimation than the existing techniques for space query size, bucket numbers, skewed data, and spatial data size.

• The KIPS Transactions:PartB
• /
• v.11B no.4
• /
• pp.421-428
• /
• 2004

There are three texture descriptors in MPEG-7 : Homogeneous Texture, Edge Histogram and Texture Browsing. In this paper, a comparative analysis is presented on the capability of MPEG-7 texture descriptors for iris recognition as part of an MPEG-7 application using descriptors. Through the experiments of comparing the clustering efficiency and error distribution of the descriptors using 560 iris images, their discriminating capabilities for different iris groups are analyzed. The results show that Homogenous Texture descriptor is the best discriminator among three descriptors to recognize the iris pattern. However, compared with the conventional iris recognition methods, it needs more efforts to enhance the results.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.7
• /
• pp.1415-1422
• /
• 2011

In this paper, full color billboards for the efficient expression of the resolution to offer dual-scanning control method, using the LED display it on a fixed pixel video signal to the pixel dot pattern was changed. And DICT(Dynamic Image Correction Technology) using the main controller in accordance with video information, histogram equalization of image gray scale values to be uniformly distributed, and dynamically improves image quality by converting the area, and a dual auto-scan input video switching controller board as the pixels in the LED Module by controlling the physical manifestation of the existing board LED pixel dots than 4 times the resolution proposes a technique that can be expressed and made it through testing verified the performance.

• Journal of the Korea Computer Industry Society
• /
• v.3 no.12
• /
• pp.1765-1774
• /
• 2002

A face recognition is currently the field which many research have been processed actively. But many problems must be solved the previous problem. First, We must recognize the face of the object taking a location various lighting change and change of the camera into account. In this paper, we proposed that new method to fund feature within fast and correct computation time after scanning PC camera and ID card picture. It converted RGB color space to YUV. A face skin color extracts which equalize a histogram of Y ingredient without the luminance. After, the method use V' ingredient which transformes V ingredient of YUV and then find the face feature. The reult of the experiment shows getting correct input face image from ID Card picture and PC camera.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.6
• /
• pp.1468-1480
• /
• 1999

In database systems, join operations are the most complex and time consuming ones which limit performance of such system. Many parallel join algorithms have been proposed for the systems. However, they did not consider data skew, such as attribute value skew (AVS) and join product skew (JPS). In the skewness environments, performance of framework for a uniform load distribution and an efficient parallel join algorithm using the framework to handle AVS and JPS. In our algorithm, we estimate data distributions of input and output relations of join operations using the sampling methodology and evaluate join cost for the estimated data distributions. Finally, using the histogram equalization method we distribute data among nodes to achieve good load balancing among nodes in the local joining phase. For performance comparison, we present simulation model of our algorithm and other join algorithms and present the result of some simulation experiments. The results indicate that our algorithm outperforms other algorithms in the skewed case.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.11 no.9
• /
• pp.777-781
• /
• 2001

This paper presents an image contrast enhancement technique for improving the low contrast images using the improved IAFC(Integrated Adaptive Fuzzy Clustering) model. The low pictorial information of a low contrast image is due to the vagueness or fuzziness of the multivalued levels of brightness rather than randomness. Fuzzy image processing has three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. Using a new model of automatic crossover point selection, optimal crossover point is selected automatically. The problem of crossover point selection can be considered as the two-category classification problem. The improved IAFC model is used to classify the image into two classes. The proposed method is applied to several experimental images with 256 gray levels and the results are compared with those of the histogram equalization technique. We utilized the index of fuzziness as a measure of image quality. The results show that the proposed method is better than the histogram equalization technique.

• Journal of KIISE:Software and Applications
• /
• v.37 no.11
• /
• pp.859-865
• /
• 2010

In this paper, a new method for finger vein recognition is proposed. Researchers are recently interested in the finger vein recognition since it is a good way to avoid the forgery in finger prints recognition and the inconveniences in obtaining images of the iris for iris recognition. The vein images are processed to obtain the line shaped vein images through the local histogram equalization and a thinning process. This thinned vein images are processed for matching, using a new matching algorithm, named HS(HeeSung) matching algorithm. This algorithm yields an excellent recognition rate when it is applied to the curve-linear images processed through a thinning or an edge detection. In our experiment with the finger vein images, the recognition rate has reached up to 99.20% using this algorithm applied to 650finger vein images(130person ${\times}$ 5images each). It takes only about 60 milliseconds to match one pair of images.