• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.363-374
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• 2010

In this paper, we propose the method for extracting Homogeneity Threshold($H_T$) and for segmenting homogeneous regions by USRG(Unseeded Region Growing) with $H_T$. The $H_T$ is a criterion to distinguish homogeneity in neighbor pixels and is computed automatically from the original image by proposed method. Theoretical background for proposed method is based on the Otsu's single level threshold method. The method is used to divide a small local part of original image int o two classes and the sum($\sigma_c$) of standard deviations for the classes to satisfy special conditions for distinguishing as different regions from each other is used to compute $H_T$. To find validity for proposed method, we compare the original image with the image that is regenerated with only the segmented homogeneous regions and show up the fact that the difference between two images is not exist visually and also present the steps to regenerate the image in order the size of segmented homogeneous regions and in order the intensity that includes pixels. Also, we show up the validity of proposed method with various results that is segmented using the homogeneity thresholds($H^*_T$) that is added a coefficient ${\alpha}$ for adjusting scope of $H_T$. We expect that the proposed method can be applied in various fields such as visualization and animation of natural image, anatomy and biology and so on.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.207-214
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• 2010

A method of the region extraction and recognition of a traffic light and speed sign board in the real road environment is proposed. Traffic light was recognized by using brightness and color information based on HSI color model. Speed sign board was extracted by measuring red intensity from the HSI color information We improve the recognition rate by performing an incline compensation of the speed sign for directions clockwise and counterclockwise. The proposed algorithm shows a robust recognition rate in the image sequence which includes traffic light and speed sign board.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.539-543
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• 2005

The research presented in this paper enables real-time 3D modeling to help make construction processes ultimately faster, more predictable and safer. Initial research efforts used an emerging sensor technology and proved its usefulness in the acquisition of range information for the detection and efficient representation of static and moving objects. Based on the time-of-flight principle, the sensor acquires range and intensity information of each image pixel within the entire sensor's field-of-view in real-time with frequencies of up to 30 Hz. However, real-time working range data processing algorithms need to be developed to rapidly process range information into meaningful 3D computer models. This research ultimately focuses on the application of safer heavy equipment operation. The paper compares (a) a previous research effort in convex hull modeling using sparse range point clouds from a single laser beam range finder, to (b) high-frame rate update Flash LADAR (Laser Detection and Ranging) scanning for complete scene modeling. The presented research will demonstrate if the FlashLADAR technology can play an important role in real-time modeling of infrastructure assets in the near future.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.327-336
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• 2004

For visual inspection system in real industrial environment, it is one of most important tasks to design fast and stable pattern matching algorithm. This paper presents an edge-based point correlation algorithm avoiding full search in visual inspection system. Conventional algorithms based on NGC(normalized gray-level correlation) have to overcome some difficulties for applying to automated inspection system in factory environment. First of all, NGC algorithms need high time complexity and thus high performance hardware to satisfy real-time process. In addition, lighting condition in realistic factory environments if not stable and therefore intensity variation from uncontrolled lights gives many roubles for applying directly NGC as pattern matching algorithm in this paper, we propose an algorithm to solve these problems from using thinned and binarized edge data and skipping full point search with edge-map analysis. A point correlation algorithm with the thinned edges is introduced with image pyramid technique to reduce the time complexity. Matching edges instead of using original gray-level pixel data overcomes NGC problems and pyramid of edges also provides fast and stable processing. All proposed methods are preyed from experiments using real images.

• Journal of KIISE
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• v.44 no.3
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• pp.295-305
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• 2017

Facial appearance is greatly influenced by illumination conditions, and therefore illumination variation is one of the factors that degrades performance of face recognition systems. In this paper, we propose a robust method for face representation under varying illumination conditions, combining non-alpha Weberface (non-alpha WF) and histogram equalization. We propose a two-step method: (1) for a given face image, non-alpha WF, which is not applied a parameter for adjusting the intensity difference between neighboring pixels in WF, is computed; (2) histogram equalization is performed to non-alpha WF, to make a uniform histogram distribution globally and to enhance the contrast. $(2D)^2PCA$ is applied to extract low-dimensional discriminating features from the preprocessed face image. Experimental results on the extended Yale B face database and the CMU PIE face database show that the proposed method yielded better recognition rates than several illumination processing methods as well as the conventional WF, achieving average recognition rates of 93.31% and 97.25%, respectively.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.99-104
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• 2002

Existing methods of object tracking use template matching, re-detection of object boundaries or motion information. The template matching method requires very long computation time. The re-detection of object boundaries may produce false edges. The method using motion information shows poor tracking performance in moving camera. In this paper, a robust object tracking algorithm is proposed, using projected motion and histogram intersection. The initial object image is constructed by selecting the regions of interest after image segmentation. From the selected object, the approximate displacement of the object is computed by using 1-dimensional intensity projection in horizontal and vortical direction. Based on the estimated displacement, various template masks are constructed for possible orientations and scales of the object. The best template is selected by using the modified histogram intersection method. The robustness of the proposed tracking algorithm has been verified by experimental results.

• Biomedical Science Letters
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• v.10 no.4
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• pp.515-521
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• 2004

To measure regional cerebral blood volume (rCBV) with perfusion MR imaging of cerebral fat embolism by neutral fat and free fatty acids in cats. Triolein (group 1, n=15), oleic acid (group 2, n=9) and linoleic acid (group 3, n=11) were infused into unilateral internal carotid artery using microcatheter through the transfemoral approach. PVA particle was used as a non-fat embolic material in a control group (group 4, n=9). Perfusion-weighted MR image was obtained at 30 minutes and 2 hours postembolization, based on T2-and diffusion-weighted images. The data of lesion and contralateral normal area were transferred to personal computer, time-to-signal intensity curve was drawn and trans for used to △R2/sup */ curve in regular order. The process in the personal computer was done by using the author's developmental image processing program and interactive data language (IDL) softwares. Statistical significance was approved by paired t-test and ANOVA. rCBV of the lesion was decreased comparing to the normal area in all groups. The ratios of rCBV were as follows (group No, at 30 minutes, at 2 hours); group 1,32％, 51％; group 2, 30％, 44％; group 3, 39％, 61％; group 4, 21％, 36％. rCBVs of 2 hours was significantly increased compared to those of 30 minutes in all groups (P<0.005). rCBV was decreased at 30 minutes in cerebral fat embolism and recovered a little, but significantly at 2 hours. Perfusion-weighted images was useful method in offering hemodynamic information in cerebral fat embolism.

• Journal of IKEEE
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• v.19 no.1
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• pp.10-17
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• 2015

In this Paper, an efficient method of FPGA based design and implementation of Sobel Edge detector block using 3-Line buffers is presented. The FPGA provides the proper and sufficient hardware for image processing algorithms with flexibility to support Sobel edge detection algorithm. A pipe-lined method is used to implement the edge detector. The proposed Sobel edge detection operator is an model using of Finite State Machine(FSM) which executes a matrix mask operation to determine the level of edge intensity through different of pixels on an image. This approach is useful to improve the system performance by taking advantage of efficient look up tables, flip-flop resources on target device. The proposed Sobel detector using 3-line buffers is synthesized with Xilinx ISE 14.2 and implemented on Virtex II xc2vp-30-7-FF896 FPGA device. Using matlab, we show better PSNR performance of proposed design in terms of 3-Line buffers utilization.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.2
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• pp.154-163
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• 2009

Incident wave angles are conventionally estimated by the directional spectrum analysis of wave data collected from in-situ sensors. The in-situ measurements are limited in monitoring incident wave angles in the wide surf zone, since the techniques are typically expensive, labor-intensive, and point-measuring. In this study, estimation of incident wave angles using wave crest features captured in digital video imagery is proposed to observe incident wave directions over the surf zone. Line signatures of wave crests having high image pixel intensities are extracted by moving an interrogation window to identify high intensity pixels in sequential video images. Wave angles are computed by taking the first derivative of the extracted crest signatures, i.e. local slope of the crest signatures in the two-dimensional physical plane. Compared to the wave angle estimates obtained by the directional spectrum analysis, video-based wave angle estimates show good agreements in general.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.90-95
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• 2014

The system design and the system performance analysis of 3D imaging laser radar system for the mapping purpose is addressed in this article. For the mapping, a push-bloom scanning method is utilized. The pulsed fiber laser with high pulse energy and high pulse repetition rate is used for the light source of laser radar system. The high sensitive linear mode InGaAs avalanche photo-diode is used for the laser receiver module. The time-of-flight of laser pulse from the laser to the receiver is calculated by using high speed FPGA based signal processing board. To reduce the walk error of laser pulse regardless of the intensity differences between pulses, the time of flight is measured from peak to peak of laser pulses. To get 3D image with a single pixel detector, Risley scanner which stirs the laser beam in an ellipsoidal pattern is used. The system laser energy budget characteristics is modeled using LADAR equation, from which the system performances such as the pulse detection probability, false alarm and etc. are analyzed and predicted. The test results of the system performances are acquired and compared with the predicted system performance. According to test results, all the system requirements are satisfied. The 3D image which was acquired by using the laser radar system is also presented in this article.