• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.956-962
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• 2018

As the study of the object feature detection from image, we explain methods to identify the species of the tree in forest using the picture taken from dron. Generally there are three kinds of methods, which are GLCM (Gray Level Co-occurrence Matrix) and Gabor filters, in order to extract the object features. We proposed the object extraction method using the statistical properties of trees in this research because of the similarity of the leaves. After we extract the sample images from the original images, we detect the objects using cross correlation techniques between the original image and sample images. Through this experiment, we realized the mean value and standard deviation of the sample images is very important factor to identify the object. The analysis of the color component of the RGB model and HSV model is also used to identify the object.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.911-921
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• 2004

Accurate minutiae extraction from input fingerprint images is one of the critical modules in robust automatic fingerprint identification system. However, the performance of a minutiae extraction is heavily dependent on the quality of the input fingerprint images. If the preprocessing is performed according to the fingerprint image characteristics in the image enhancement step, the system performance will be more robust. In this paper, we propose a knowledge-based preprocessing method, which extracts S features (the mean and variance of gray values, block directional difference, orientation change level, and ridge-valley thickness ratio) from the fingerprint images and analyzes image quality with Ward's clustering algorithm, and enhances the images with respect to oily/neutral/dry characteristics. Experimental results using NIST DB 4 and Inha University DB show that clustering algorithm distinguishes the image Quality characteristics well. In addition, the performance of the proposed method is assessed using quality index and block directional difference. The results indicate that the proposed method improves both the quality index and block directional difference.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.3
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• pp.181-189
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• 2004

This paper describes the method for detecting vehicles in the rear and rear-side at night by using headlight features. A headlight is the outstanding feature that can be used to discriminate a vehicle from a dark background. In the segmentation process, a night image is transformed to a binary image that consists of black background and white regions by gray-level thresholding, and noise in the binary image is eliminated by a morphological operation. In the feature extraction process, the geometric features and moment invariant features of a headlight are defined, and they are measured in each segmented region. Regions that are not appropriate to a headlight are filtered by using geometric feature measurement. In region classification, a pair of headlights is detected by using relational features based on the symmetry of a pair of headlights. Experimental results show that this method is very applicable to an approaching vehicle detection system at nighttime.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.217-220
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• 2005

Internal cities such as gray level been enclosed to building forest are paying a lot of efforts and expenses to change to green city toot park and street tree get put together. By the example, 'GREEN CITY of PUSAN 21' progress to decorate army facilities like the park, and to plant street trees in several places of city plan in Pusan. And urban environment that big citys of advanced nation are agreeable is making in the large park and road street trees at several places in downtown. Because price of tree for the park is very expensive, tree management system was all-important. In this paper, Motes deliver the sensor information in each tree through radio sensor network by server side. This information can use in state grasping of tree, harmful insects courtesy call etc and this system design was suggested to inform to mode of life administration scholars.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.6
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• pp.499-506
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• 2004

The copper foil surface inspection system is necessary for the factory automation and product quality. The developed system is composed of the high speed line scan camera, the image capture board and the processing computer. For the system resource utilization and real-time processing, multi-threaded architecture is introduced. There are one image capture thread, 2 or more defect detection threads, and one defect communication thread. To process the high-speed input image data, the I/O overlap is used through the double buffering. The defect is first detected by the predetermined threshold. To cope with the light irregularity, the compensation process is applied. After defect detection, defect type is classified with the defect width, eigenvalue ratio of the defect covariance matrix and gray level of defect. In experiment, for high-speed input image data, real-time processing is possible with multi -threaded architecture, and the 89.4% of the total 141 defects correctly classified.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.579-586
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• 2002

The edge descriptor proposed by MPEG-7 standard is a representative approach for the contents-based image retrieval using the edge information. In the edge descriptor, the edge information is the edge histogram derived from a gray-level value image. This paper proposes a new method which extracts color edge information from color images and a new approach for the contents-based image retrieval based on the color edge histogram. The poposed method and technique are applied to image retrieval of the e-catalogue. For the evaluation, the results of image retrieval using the proposed approach are compared with those of image retrieval using the edge descriptor by MPEG-7 and the statistics shows the efficiency of the proposed method. The proposed color edge model is made by combining the R,G,B channel components vectorially and by characterizing the vector norm of the edge map. The color edge histogram using the direction of the color edge model is subsequently used for the contents-based image retrieval.

• The Journal of Information Technology
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• v.6 no.1
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• pp.71-84
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• 2003

In this paper, it is presented the efficient system for data recognition using the proposed binary code images. The proposed algorithm finds the position of binary image. Through the process of the block region classification, it is classified each block with the edge region using the value of gray level only. Each block region is divided horizontal and vertical edge region. If horizontal edge region blocks are classified over six blocks in any region, the proposed algorithm should search the vertical edge region in the start point of the horizontal edge region. If vertical edge region blocks were found over ten blocks in vertical region, the code image would found. Practical code region is acquired from the rate of the total edge region that is computed from the binary image that is processed with the average value. In case of the wrong rate, it is restarted the code search in the point after start point and the total process is followed. It has a short time than the before process time because it had classified block information. The block processing is faster thant the total process. The proposed system acquires the image from the digital camera and makes binary image from the acquired image. Finally, the proposed system extracts various characters from the binary image.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.492-503
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• 2008

With the recent development and increasing importance of personal identification systems, biometric technologies with less risk of loss or unauthorized use are being popularized rapidly. In particular, because of their high identification rate and convenience, fingerprint identification systems are being used much more commonly than other biometric systems such as iris recognition, face recognition and vein pattern recognition. However, a fingerprint identification system has the problem that artificially forged finger-prints can be used as input data. Thus, in order to solve this problem, the present study proposed a method for detecting forged fingerprints by measuring the degree of attenuation when the light from an optical fingerprint sensor passes through the finger and analyzing changes in the transmission of light over stages at fixed intervals. In order to prove improvement in the performance of the proposed system, we conducted an experiment that compared the system with an existing multi-sensor recognition system that measures also the temperature of fingerprint. According to the results of the experiment, the proposed system improved the forged fingerprint detection rate by around 32.6% and this suggests the possibility of solving the security problem in fingerprint identification systems.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.266-274
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• 2009

An abdominal aortic aneurysm occurs most commonly in older individuals (between 65 and 75), and more in men and smokers. The most important complication of an abdominal aortic aneurysm is rupture, which is most often a fatal event. An abdominal aortic aneurysm weakens the walls of the blood vessel, leaving it vulnerable to bursting open, or rupturing, and spilling large amounts of blood into the abdominal cavity. surface modeling is very useful to surgery for quantitative analysis of abdominal aortic aneurysm. the 3D representation and surface modeling an abdominal aortic aneurysm structure taken from Multi Detector Computed Tomography. The construction of the 3D model is generally carried out by staking the contours obtained from 2D segmentation of each CT slice, so the quality of the 3D model strongly defends on the precision of segmentation process. In this work we present deformable model algorithm. deformable model is an energy-minimizing spline guided by external constraint force. External force which we call Gradient Vector Flow, is computed as a diffusion of a gradient vectors of gray level or binary edge map derived from the image. Finally, we have used snakes successfully for abdominal aortic aneurysm segmentation the performance of snake was visually and quantitatively validated by experts.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.748-753
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• 2012

In this paper, Face recognition algorithm is designed based on optimized pRBFNNs pattern classifier using three-dimensional scanner. Generally two-dimensional image-based face recognition system enables us to extract the facial features using gray-level of images. The environmental variation parameters such as natural sunlight, artificial light and face pose lead to the deterioration of the performance of the system. In this paper, the proposed face recognition algorithm is designed by using three-dimensional scanner to overcome the drawback of two-dimensional face recognition system. First face shape is scanned using three-dimensional scanner and then the pose of scanned face is converted to front image through pose compensation process. Secondly, data with face depth is extracted using point signature method. Finally, the recognition performance is confirmed by using the optimized pRBFNNs for solving high-dimensional pattern recognition problems.