• Bulletin of the Korean Mathematical Society
• /
• v.48 no.5
• /
• pp.939-949
• /
• 2011

In this paper we give two matching theorems of Ky Fan type concerning open or closed coverings of nonempty convex sets in a topological vector space. One of them will permit us to put in evidence, when X and Y are convex sets in topological vector spaces, a new subclass of KKM(X, Y) different by any admissible class $\mathfrak{u}_c$(X, Y). For this class of set-valued mappings we establish a KKM-type theorem which will be then used for obtaining existence theorems for the solutions of two types of simultaneous relation problems.

• Proceedings of the IEEK Conference
• /
• 1998.06a
• /
• pp.733-736
• /
• 1998

In this paper, we propose a new method for content-based retrieval system using wavelet transform and correlation, which has were used in signal processing and image compressing. The matching method is used not perfect matching but similar matching. Used feature vector is the lowest frequency(LL) itself, energy value, and edge information of 4-layer, after computng a 4-layer 2-D fast wavelet transform on image. By the proosed algorithm, we got the result that was faste rand more accurate than the traditional algorithm. Because used feature vector was compressed 256:1 over original image, retrieval speed was highly improved. By using correlation, moving object with size variation was reterieved without additional feature information.

• Journal of Information Technology Applications and Management
• /
• v.12 no.4
• /
• pp.93-104
• /
• 2005

Recently, RFID/USN is one of fundamental technologies in information and communications networks. Low-Rate WPAN, IEEE802.15.4 is a low-cost communication network that allows wireless connectivity in applications with limited Power and relaxed throughput requirements. Its applications are building automation, personal healthcare, industrial control, consumer electronics, and so on. Some applications require location information. Of course location awareness is useful to improve usability of data Low-Rate WPAN Is regarded as a key specification of the sensor network with the characteristics of wireless communication, computing, energy scavenging, self-networking, and etc. Unfortunately ZigBee alliance propose a lot of applications based on location aware technologies, but the specification and low-rate WPAN devices don't support anything about location-based services. RSSI ( Received Signal Strength indication) is for energy detection to associate, channel selection, and etc. RSSI is used to find the location of a potable device in WLAN. In this paper we studied indoor location awareness using vector matching of RSSI in low-Rate wireless PAN. We analyzed the characteristics of RSSI according to distance and experimented location awareness. We implemented sensor nodes with different shapes and configured the sensor network for the location awareness with 4 fixed nodes and a mobile node. We try to contribute developing location awareness method using RSSI in 3-dimension space.

• Journal of Biomedical Engineering Research
• /
• v.23 no.2
• /
• pp.101-107
• /
• 2002

This paper presents a segmentation algorithm to extract endocardial contour and epicardial contour of left ventricle in MR Cardiac images. The algorithm is based on a generalized gradient vector flow(GGVF) snake and a prediction of initial contour(PIC). Especially. the proposed algorithm uses physical characteristics of endocardial and epicardial contours, cross profile correlation matching(CPCM), and a mixed interpolation model. In the experiment, the proposed method is applied to short axis MR cardiac image set, which are obtained by Siemens, Medinus, and GE MRI Systems. The experimental results show that the proposed algorithm can extract acceptable epicardial and endocardial walls. We calculate quantitative parameters from the segmented results, which are displayed graphically. The segmented left vents role is visualized volumetrically by surface rendering. The proposed algorithm is implemented on Windows environment using Visual C ++.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.766-771
• /
• 2002

Automatic change detection based on the vector-to-raster comparison is hard especially in high-resolution image. This paper proposes a method to designate roads in high-resolution image in sequential manner using the information from vector map in which Hough transform is used for reliability. By its linearity, the road of urban areas in a vector map can be easily parameterized. Following some pre-processing to remove undesirable objects, we obtain the edge map of raster image. Then the edge map is transformed to a parameter space to find the selected road from vector map. The comparison is done in the parameter space to find the best matching. The set of parameters of a road from vector map is treated as the constraints to do matching. After designating the road, we may overlay it on the raster image for precise monitoring. The results can be used for detection of changes in road object in a semi-automatic fashion.

• The KIPS Transactions:PartB
• /
• v.11B no.3
• /
• pp.247-256
• /
• 2004

In this paper, we propose the prediction search algorithm for block matching using the temporal/spatial correlation of the video sequence and the renter-biased property of motion vectors The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(Sum of Absolute Difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate pint in each search region and the predicted motion vector from the neighbour blocks of the current frame. And the searching process after moving the starting point is processed a adaptive search pattern according to the magnitude of motion vector Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved up to the 0.75dB as depend on the video sequences and improved about 0.05∼0.34dB on an average except the FS (Full Search) algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.8C
• /
• pp.772-781
• /
• 2009

This paper proposes a novel algorithm for the efficient classification and retrieval of medical images. After color and edge features are extracted from medical images, these two feature vectors are then applied to a multi-class Support Vector Machine, to give membership vectors. Thereafter, the two membership vectors are combined into an ensemble feature vector. Also, to reduce the search time, Correlated Categories Vector is proposed for similarity matching. The experimental results show that the proposed system improves the retrieval performance when compared to other methods.

• Communications for Statistical Applications and Methods
• /
• v.15 no.4
• /
• pp.543-549
• /
• 2008

Inspired by using a robust loss function in the support vector machine regression to control training error and the idea of robust template matching with M-estimator, Chen (2004) applies M-estimator techniques to gaussian radial basis functions and form a new class of robust kernels for the support vector machines. We are specially interested in the shape of the Huber's M-estimator in this context and propose a way to find the shape parameter of the Huber's M-estimating function. For simplicity, only the two-class classification problem is considered.

• Proceedings of the Korean Institute of Communication Sciences Conference
• /
• 1986.10a
• /
• pp.76-78
• /
• 1986

In this paper a fst block matching algorithm using integral projection is peoposed to fing the motion vector. In this case we can reduce the computation time greatly. Especially when we apply the integral projection to the OTS method, the averagr ratio of the computational savings is about 4.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.418-422
• /
• 2009

Generally, algorithms for generating disparity maps can be clssified into two categories: region-based method and feature-based method. The main focus of this research is to generate a disparity map with an accuracy depth information for 3-dimensional reconstructing. Basically, the region-based method and the feature-based method are simultaneously included in the proposed algorithm, so that the existing problems including false matching and occlusion can be effectively solved. As a region-based method, regions of false matching are extracted by the proposed MMAD(Modified Mean of Absolute Differences) algorithm which is a modification of the existing MAD(Mean of Absolute Differences) algorithm. As a feature-based method, the proposed method eliminates false matching errors by calculating the vector with SIFT and compensates the occluded regions by using a pair of adjacent SIFT matching points, so that the errors are reduced and the disparity map becomes more accurate.