• Journal of Information Display
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• v.3 no.2
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• pp.19-25
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• 2002

In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.111-119
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• 2013

Face recognition has recently become one of the most popular research areas in the fields of computer vision, machine learning, and pattern recognition because it spans numerous applications, such as access control, surveillance, security, credit-card verification, and criminal identification. In this paper, we propose a simple descriptor called an ECSP(Extended Center-Symmetric Pattern) for illumination-robust face recognition. The ECSP operator encodes the texture information of a local face region by emphasizing diagonal components of a previous CS-LBP(Center-Symmetric Local Binary Pattern). Here, the diagonal components are emphasized because facial textures along the diagonal direction contain much more information than those of other directions. The facial texture information of the ECSP operator is then used as the input image of an image covariance-based feature extraction algorithm such as 2D-PCA(Two-Dimensional Principal Component Analysis). Performance evaluation of the proposed approach was carried out using various binary pattern operators and recognition algorithms on the Yale B database. The experimental results demonstrated that the proposed approach achieved better recognition accuracy than other approaches, and we confirmed that the proposed approach is effective against illumination variation.

• Fashion & Textile Research Journal
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• v.18 no.4
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• pp.468-476
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• 2016

Recent advancements in optics technology enable us to realize fast scans of hands using two-dimensional (2D) image scanners. In this paper, we propose an automatic hand measurement system using 2D image scanners for customized glove production. To develop the automatic hand measurement system, firstly hand scanning devices has been constructed. The devices are designed to block external lights and have user interface to guide hand posture during scanning. After hands are scanned, hand contour is extracted using binary image processing, noise elimination and outline tracing. And then, 19 hand landmarks are automatically detected using an automatic hand landmark detection algorithm based on geometric feature analysis. Then, automatic hand measurement program is executed based on the automatically extracted landmarks and measurement algorithms. The automatic hand measurement algorithms have been developed for 18 hand measurements required for custom-made glove pattern making. The program has been coded using the C++ programming language. We have implemented experiments to demonstrate the validity of the system using 11 subjects (8 males, 3 females) by comparing automatic 2D scan measurements with manual measurements. The result shows that the automatic 2D scan measurements are acceptable in the customized glove making industry. Our evaluation results confirm its effectiveness and robustness.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.131-139
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• 2016

Recognition of human motions has become a main area of computer vision due to its potential human-computer interface (HCI) and surveillance. Among those existing recognition techniques for human motions, head detection and tracking is basis for all human motion recognitions. Various approaches have been tried to detect and trace the position of human head in two-dimensional (2D) images precisely. However, it is still a challenging problem because the human appearance is too changeable by pose, and images are affected by illumination change. To enhance the performance of head detection and tracking, the real-time three-dimensional (3D) data acquisition sensors such as time-of-flight and Kinect depth sensor are recently used. In this paper, we propose an effective feature extraction method, called adaptive local binary pattern (ALBP), for depth image based applications. Contrasting to well-known conventional local binary pattern (LBP), the proposed ALBP cannot only extract shape information without texture in depth images, but also is invariant distance change in range images. We apply the proposed ALBP for head detection and tracking in depth images to show its effectiveness and its usefulness.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.593-594
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• 2015

We present our analysis results for an updated orbital ephemeris for the dipping low mass X-ray binary 4U 1624-49, using the light curve collected by the All Sky Monitor (ASM) on board the Rossi X-ray Timing Explorer (RXTE) and the Monitor of All-Sky X-ray Image (MAXI). To make clear dip profiles, the light curve from the ASM and the MAXI were divided into ten 500d segments and four 400d segments for ASM and MAXI light curves, respectively, and folded with the linear ephemeris proposed by Smale et al. (2001). The phases of dip centers were determined by the method adopted from Hu et al. (2008). The phase drift was then fitted with a linear function. We obtained an updated orbital period of 0.869896(1) d and a phase zero epoch of JD 2450088.6618(57). No clear orbital period derivative is detected with a 2-sigma upper limit of $1.4{\times}10^{-6}(yr)^{-1}$ from a quadratic curve fitting of the dip phase evolution.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.868-874
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• 2007

This paper proposes an efficient partial matching system and representation by using a region-based method for 2D image, and we applied to an extraction of the ROI(Region of Interest) according to its matching score. The matching templates consist of the global pattern and the local one. The global pattern can make it by using region-based relation between center region and its rest regions in an object. And, the local pattern can be obtained appling to the same method as global, except relation between objects. As the templates can be normalized, we use this templates for extraction of ROI with invariant to size and position. And, our system operates only one try to match, due to normalizing of region size. To use our system for searching and examining if it's the ROI by evaluating the matching function, at first, we are searching to find candidate regions with the global template. Then, we try to find the ROI among the candidates, and it works this time by using the local template. We experimented to the binary and the color image respectively, they showed that the proposed system can be used efficiently for representing of the template and the useful applications, such as partially retrievals of 2D image.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.927-930
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• 2000

Visual features of lip area play an important role in the visual speech information. We are concerned about correct lip area as region of interest (ROI). In this paper, we propose a robust and fast method for locating the mouth corners. Also, we define a region of interest at mouth during speech. A method, which we have used, only uses the horizontal and vertical image operators at mouth area. This searching is performed by fitting the ROI-template to image with illumination control. Most of the lip extraction algorithms are dependent on luminosity of image. We just used the binary image where the variable threshold is applied. The variable threshold varies to illumination condition. In order to control those variations, the gray-tone is converted to binary image by threshold, which is obtained through Multiple Linear Regression Analysis (MLRA) about divided 2D special region. Thus we obtained the region of interest at mouth area, which is the robust extraction about illumination. A region of interest is automatically extracted.

• Journal of Industrial Technology
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• v.19
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• pp.403-408
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• 1999

An efficient method is developed for classifying fingerprint data based on 2-D discrete wavelet transform. Fingerprint data is first converted to a binary image. Then a multi-level 2-D wavelet transform is performed. Vertical and horizontal subbands of the transformed data show typical energy distribution patterns relevant to the fingerprint categories. The proposed method with moderate level of wavelet transform is successful in classifying fingerprints into 5 different types. Finer classification is possible by higher frequency subbands and closer analysis of energy distribution.

• Journal of Biomedical Engineering Research
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• v.26 no.2
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• pp.73-86
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• 2005

We need to flatten the brain cortex to smooth surface, sphere, or 2D plane in order to view the buried sulci. The rendered 3D surface of the segmented white matter and gray matter does not have the topology of a sphere due to the partial volume effect and segmentation error. A surface without correct topology may lead to incorrect interpretation of local structural relationships and prevent cortical unfolding. Although some algorithms try to correct topology, they require heavy computation and fail to follow the deep and narrow sulci. This paper proposes a method that corrects topology of the rendered surface fast, accurately, and automatically. The proposed method removes fractions beside the main surface, fills cavities in the inside of the main surface, and removes handles in the surface. The proposed method to remove handles has three-step approach. Step 1 performs smoothing operation on the rendered surface. In Step 2, vertices of sphere are gradually deformed to the smoothed surfaces and finally to the boundary of the segmented white matter and gray matter. The Step 2 uses multi-resolutional approach to prevent the deep sulci from geometrical intersection. In Step 3, 3D binary image is constructed from the deformed sphere of Step 2 and 3D surface is regenerated from the 3D binary image to remove intersection that may happen. The experimental results show that the topology is corrected while principle sulci and gyri are preserved and the computation amount is acceptable.

• Journal of Biosystems Engineering
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• v.26 no.3
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• pp.279-286
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• 2001

The purpose of this study were to organize a sorting system, to develop an algorithm of image processing for the shape sorting, and to finally develop a scientific and objective shape sorting system of Korean Red-Ginseng for mechanization of the shape sorting. The results of this study are followed. 1. The shape sorting system of Korean Red-Ginseng consists of a control computer, a color CCD camera(WV-CP4110) for image processing, an image processing board(DT3153), and an image acquisition unit. 2. Many image processing skill, such as sliding, stretching, threshold, binary and D$\sub$t/ were used to analyze the shape sorting factors of Korean Red-ginseng. 3. The sorting accuracy of the shape sorting system for the Korean Red-Ginseng was 74.7%. It is 21.1% lower than that of human inspector. Although the system has low accuracy, using more cameras may improve its sorting accuracy.