Prof. Jongan Park Profile

Prof. Jongan Park

at Chosun Univ

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Author

Publications (13)

Proceedings Article | 28 May 2004 Paper

Multiple vehicle tracking using invariant moments and Hough transform

Seung Hak Rhee, Muhammad Bilal Ahmad, Seung-Jin Park, Kyoung-Ju Beak, Jong-An Park

Proceedings Volume 5298, (2004) https://doi.org/10.1117/12.521595

KEYWORDS: Image segmentation, Hough transforms, Detection and tracking algorithms, Cameras, Image processing algorithms and systems, Binary data, Image processing, Pattern recognition, Optical flow, Roads

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Proceedings Article | 28 May 2004 Paper

Histogram as a measure of shape matching

Min Hyuk Chang, Kyung-Sik Seo, Hye-Jin Park, Jong-An Park

Proceedings Volume 5298, (2004) https://doi.org/10.1117/12.521596

KEYWORDS: Image retrieval, Databases, Feature extraction, Visualization, Distance measurement, Information visualization, Binary data, Image segmentation, Shape analysis, Machine vision

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Proceedings Article | 29 March 2004 Paper

Shape matching using the modified histogram-based chain code

Hye Jin Park, Min-Seok Ji, Jae-Taeg Ha, Jong-Hun Chun, Jong An Park

Proceedings Volume 5283, (2004) https://doi.org/10.1117/12.520672

KEYWORDS: Image retrieval, Databases, Distance measurement, Feature extraction, Finite element methods, Computer programming, Image segmentation, Electronics, Communication engineering, Digital imaging

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Proceedings Article | 29 March 2004 Paper

Collision avoidance of two moving objects using the anticipated path

Seung Hak Rhee, Muhammad Bilal Ahmad, Seung-Jin Park, Kyoung-Ju Beak, Jong An Park

Proceedings Volume 5283, (2004) https://doi.org/10.1117/12.520671

KEYWORDS: Collision avoidance, Detection and tracking algorithms, Image segmentation, Image processing algorithms and systems, Binary data, Cameras, Image processing, Sensors, Electronics, Intelligence systems

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Proceedings Article | 23 June 2003 Paper

Shape contour description using modified radius-vector function

Seung-Jin Park, Hae-Jin Park, Jong-An Park

Proceedings Volume 5150, (2003) https://doi.org/10.1117/12.502356

KEYWORDS: Visualization, Information visualization, Databases, Shape analysis, Feature extraction, Binary data, Stars, Image analysis, Image retrieval, Object recognition

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Proceedings Article | 30 August 2002 Paper

Power-spectrum-based shape matching for MPEG-7

Seung Hak Rhee, Muhammad Ahmad, Jong-An Park

Proceedings Volume 4925, (2002) https://doi.org/10.1117/12.481563

KEYWORDS: Fourier transforms, Databases, Multimedia, Shape analysis, Feature extraction, Digital imaging, Statistical methods, Visualization, Image registration, Detection and tracking algorithms

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Proceedings Article | 30 August 2002 Paper

Movement information measurement based on Boolean edge detection and modified HT

Min-Hyuk Chang, In-Jeon Park, Kyung Lim, Tae-Kyung Ban, Jong-An Park

Proceedings Volume 4925, (2002) https://doi.org/10.1117/12.481562

KEYWORDS: Optical flow, Edge detection, Sensors, Hough transforms, Binary data, Image segmentation, Motion estimation, Statistical analysis, Detection and tracking algorithms, Optical tracking

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Proceedings Article | 20 December 2001 Paper

IEC 61883 and AV/C CTS-based IEEE 1394 digital home appliances control

Il-Jung Kim, Soo-Kyung Yang, Seung Hak Rhee, Ik Soo Choy, Jong-An Park

Proceedings Volume 4674, (2001) https://doi.org/10.1117/12.451068

KEYWORDS: Control systems, Human-machine interfaces, Video, Digital cameras, Cameras, Standards development, Multimedia, Data transmission, Digital electronics, Data communications

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Proceedings Article | 4 October 2001 Paper

Optical flow measurment on Boolean edge detection and Hough transform

Muhammad Ahmad, Seung Hak Rhee, Ik Soo Choy, Jong-An Park, Tae-Sun Choi

Proceedings Volume 4564, (2001) https://doi.org/10.1117/12.444085

KEYWORDS: Optical flow, Edge detection, Hough transforms, Sensors, Binary data, Motion estimation, Image segmentation, Optical testing, Numerical analysis, Image processing

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Motion estimation is one of the fundamental problems in digital video processing. One of the most notable approaches of motion estimation is based on the estimation of a measure of the change of image brightness in the frame sequence commonly referred to as optical flow. The classical approaches for finding optical flow have many drawbacks. The numerical methods or least square methods for solving optical flow constrains are susceptible to errors in the cases of occlusion and of noise. Two moving objects having common border causes confliction in the velocities, and taking their averages yields a less satisfactory optical flow estimation. The wrong detection of moving boundary, as motion is usually not homogeneous and the inexact contour measurements of moving objects are the other problems of optical flow methods. Therefore, information such as color and edges along with optical flow has been used in the literature. Further, the classical methods need lot of calculations and computations for optical flow measurements. In this paper, we proposed a method, which is very fast and gives better moving information of the objects in the image sequences. The possible locations of moving objects are found first, and then we apply the Hough Transform only on the detected moving regions to find the optical flow vectors for those regions only. So we save lot of time for not finding optical flow for the still or background parts in the image sequences. The new Boolean based edge detection is applied on the two consecutive input images, and then the differential edge image of the resulting two edge maps is found. A mask for detecting the moving regions is made by dilating the differential edge image. After getting the moving regions in the image sequence with the help of the mask obtained already, we use the Hough Transform and voting accumulation methods for solving optical flow constraint equations. The voting based Hough transform avoids the errors associated with least squares techniques. Calculation of a large number of points along the constraint line is also avoided by using the transformed slope-intercept parameter domain. The simulation results show that the proposed method is very effective for extracting optical flow vectors and hence tracking moving objects in the images.

Proceedings Article | 11 October 2000 Paper

Moving information extraction for moving-object tracking

Hyung-Bum Kim, Min-Hyuk Chang, Sung-Kwan Kang, Jong-Hun Chun, Jong-An Park

Proceedings Volume 4210, (2000) https://doi.org/10.1117/12.403802

KEYWORDS: Optical flow, Image processing, Optical tracking, Detection and tracking algorithms, Hough transforms

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Proceedings Article | 28 June 2000 Paper

Characteristic extraction of face using DWT and recognition based on neural networks

Hyung-Bum Kim, Chun-Hwan Lim, SeungJin Park, Jong-An Park

Proceedings Volume 4080, (2000) https://doi.org/10.1117/12.389443

KEYWORDS: Image segmentation, Discrete wavelet transforms, Neural networks, Facial recognition systems, Feature extraction, Wavelets, Detection and tracking algorithms, Nose, Image processing algorithms and systems, Mouth

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Proceedings Article | 25 March 1998 Paper

ANN learning algorithm using the offset control parameter

Chun-Hwan Lim, Younggil Shin, Jaimin Ryu, Jong-An Park

Proceedings Volume 3390, (1998) https://doi.org/10.1117/12.304855

KEYWORDS: Neurons, Neural networks, Data hiding, Systems modeling, Complex systems, Logic, Computer simulations, Control systems, Device simulation, Image classification

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Proceedings Article | 22 July 1997 Paper

Depth information on moving objects using stereo vision

Ik Soo Choy, Yonggil Sin, Jong-An Park

Proceedings Volume 3074, (1997) https://doi.org/10.1117/12.280633

KEYWORDS: Cameras, Stereo vision systems, Imaging systems, Digital signal processing, Image analysis, Digital imaging, Stereoscopic cameras, CCD cameras, Image filtering, Vision geometry

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Showing 5 of 13 publications

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