• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.999-1002
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• 2013

There are numerous image processing systems these are usually depend on high performance processors. However, systems using high performance processors might not be proper to mobile applications or low-power systems. Therefore, more efficient methodology for image processing is required for variable applications. This paper proposed pre-processing method using intra prediction concept in order to reduce processing range in a image picture(frame) and entire processing time. Also, the system configuration based on intra prediction hardware core and implementation result of the hardware core are presented in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1058-1070
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• 2014

There are two major ways to implement depth estimation, multiple image depth estimation and single image depth estimation, respectively. The former has a high hardware cost because it uses multiple cameras but it has a simple software algorithm. Conversely, the latter has a low hardware cost but the software algorithm is complex. One of the recent trends in this field is to make a system compact, or even portable, and to simplify the optical elements to be attached to the conventional camera. In this paper, we present an implementation of depth estimation with a single image using a graphics processing unit (GPU) in a desktop PC, and achieve real-time application via our evolutional algorithm and parallel processing technique, employing a compute shader. The methods greatly accelerate the compute-intensive implementation of depth estimation with a single view image from 0.003 frames per second (fps) (implemented in MATLAB) to 53 fps, which is almost twice the real-time standard of 30 fps. In the previous literature, to the best of our knowledge, no paper discusses the optimization of depth estimation using a single image, and the frame rate of our final result is better than that of previous studies using multiple images, whose frame rate is about 20fps.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.7
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• pp.37-42
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• 2008

In this paper, a real-time multiview video coding system using fast disparity estimation is proposed. In the multiview encoder, adaptive disparity-motion estimation (DME) for an effective 3-dimensional (3D) processing are proposed. That is, by adaptively predicting the mutual correlation between stereo images in the key-frame using the proposed algorithm, the bandwidth of stereo input images can be compressed to the level of a conventional 2D image and a predicted image also can be effectively reconstructed using a reference image and adaptive disparity vectors. Also, in multiview decoder, intermediate view reconstruction (IVR) using adaptive disparity search algorithm (DSA) for real-time multiview video processing is proposed. The proposed IVR can reduce a processing time of disparity estimation by selecting adaptively disparity search range. Accordingly, the proposed multiview video coding system is able to increase the efficiency of the coding rate and improve the resolution.

• Korean Journal of Remote Sensing
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• v.9 no.1
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• pp.37-49
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• 1993

In this research, the WEF AX and APT(Automatic Picture Transmission) data receiving and image processing software using PC/AT called WADIPS(WEFAX and APT Data Integrated Processing System) Software has been developed. The main functions of WADIPS software are follow : 1) Real time receiving and saving to hard disk of WEFAX and APT data 2) B/W(Black and White) and false color display 3) Image enhancement using histogram stretch and color control 4) 2-4 times zooming 5) Hard copy of data using dithering and patterning 6) Animation 7) File management 8) On line help. WADIPS can be used in the offices or persons need real time meteorological information and education offices to teach the image processing technique and general characteristics of meteorological satellites.

• Journal of Biomedical Engineering Research
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• v.8 no.2
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• pp.117-117
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• 1987

The medical image processing system is intended for a diverse set of users in the medical Imaging Parts. This system consists of a 640 Kbyte IBM-PC/AT with 30 Mbyte hard disk, special purpose image processor with video input devices and display monitor. Image may be recorded and processed in real time at sampling rate up to 10 MHz. This system provides a wide range of image enhancement processing facilities via a menu-driven software packages. These facilities include point by point processing, image averaging, convolution filter and subtraction.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.177-179
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• 2005

This paper suggests a high-speed blurred blob image inspection algorithm. When we inspect some products using high-resolution camera, the detected blob images usually have severe blur. And the blur makes it hard to detect an object. There are many blur-processing algorithms, but most of them have no real-time property for high-speed applications at all. In this paper, an MMX technology based algorithm is suggested. The suggested algorithm was found to be effective to detect the blurred blob images via many simulations and long time real-plant experiments.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.426-439
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• 1996

In this paper, we propose a simple algorithm to calculate the numbers of the passing cars by using an image processing sensor for the digital black and white images with 256 tone level. Shadow is one of the most troublesome factor in image processing. By differencing the tone level, we cannot discriminate between the body of the car and its shadow. In our proposed algorithm, the area of the shadow is excluded by recognizing the position of each traffic lane. For real-time operation and simple calculation, two lines of the tone level are extracted and the existences of cars are recognized. In the experimental application on a high-way, the recognition rate of the real-time operation is more than 94%.

• Journal of IKEEE
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• v.20 no.3
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• pp.209-219
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• 2016

SVM is a machine learning method used for image processing. It is well known for its high classification performance. We have to perform multiple MAC operations in order to use SVM for image classification. However, if the resolution of the target image or the number of classification cases increases, the execution time of SVM also increases, which makes it difficult to be performed in real-time applications. In this paper, we propose an hardware architecture which enables real-time applications using SVM classification. We used parallel architecture to simultaneously calculate MAC operations, and also designed the system for several feature extractors for compatibility. RBF kernel was used for hardware implemenation, and the exponent calculation formular included in the kernel was modified to enable fixed point modelling. Experimental results for the system, when implemented in Xilinx ZC-706 evaluation board, show that it can process 60.46 fps for $1360{\times}800$ resolution at 100MHz clock frequency.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.223-230
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• 2006

A window-based image processing is an elementary part of image processing area. Because window-based image processing is computationally intensive and data intensive, it is hard to perform ail of the operations of a window-based image processing in real-time by using a software program on general-purpose computers. This paper proposes a parallel hardware architecture that can perform a window-based image processing in real-time using FPGA(Field Programmable Gate Array). A dynamic threshold circuit and a local histogram equalization circuit of the proposed architecture are designed using VHDL(VHSIC Hardware Description Language) and implemented with an FPGA. The performances of both implementations are measured.

• The Journal of the Acoustical Society of Korea
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• v.18 no.3
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• pp.79-87
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• 1999

In this paper, we reconstruct an algorithm of sound image control for real-time processing and implement a real-time system using digital signal processing board based on TMS320C40. The performance of real-time sound image control system was evaluated by a listening test. The results of the test showed that localized sound image can be perceived by headphone and speaker, and result of test by headphone was better than that of speaker. In the results of test of elevation perception, result of perception between left and right were better than those for differentiating between front and back, and the moving sound image was better than the fixed sound image.