• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.555-562
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• 2007

In order to display Bayer input stream received from CMOS image sensor to the display device, image signal processing must be performed. That is, the hardware performing the image signal processing for Bayer data is called ISP(Image Signal Processor). We can see real image through ISP processing. ISP executes functionalities for gamma correction, interpolation, color space conversion, image effect, image scale, AWB, AE and AF. In this paper, we obtained the optimum algorithm through software verification of ISP module for CMOS camera image sensor and described using VHDL and verified in ModelSim6.0a simulator. Also we downloaded into Xilinx XCV-1000e for the designed ISP module and completed the board level verification using PCI interface.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.149-153
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• 2004

A Impulse denosing filter design of image for the faster processing time and system compatibility using DSP processor is presented on this paper The system hardware is composed of the stand-alone board with 32 bits DSP processor and vision board for image data acquisition with NTSC CCD camera, and the host computer controls them. The denoising method uses the adaptive median filter. The experiment result is that the system leads to denosing effect as 90% and PSNR 22㏈

• Journal of Satellite, Information and Communications
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• v.12 no.2
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• pp.56-60
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• 2017

This paper describes the design and implementation of fall-down detection algorithm based on image processing. The fall-down detection algorithm separates objects by using background subtraction and binarization after grayscale conversion of the input image acquired by the camera, and recognizes the human body by using labeling operation. The recognized human body can be monitored on the display image, and an alarm is generated when fall-down is detected. By using computer simulation, the proposed algorithm has shown a detection rate of 90%. We verify the feasibility of the proposed system by verifying the function by using the prototype test implemented on the DSP image processing board.

• Journal of Animal Environmental Science
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• v.6 no.1
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• pp.15-22
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• 2000

A monitoring and the forecasting system for the swine delivery was developed using CCD camera multi-function board microphone and data-recorder equipped on a personal computer. For the swine delivery monitoring and forecasting factors four factors were selected such as genitalia swine body shape breast color and sound. Image of physical variation of body shape, shape and color of genitalia area and color of breast of pregnant sow were grabbed using the CCD color camera and multi-function board and variation of voice of pregnant sow was acquired using microphone and data recorder. Acquired information of image and voice were analyzed using a custom developed algorithm and program. The result of the forecasting efficiency of swine delivery was 89%, 71% and 100% using the variation of genitalia are the body shape and the voice of pregnant sow. respectively. The efficiency of image processing was 100% for the delivery detection when the piglet was delivered half of its body from genitalia of pregnant sow, The monitoring and forecasting system informed the estimated time of the delivery of swine to a farm manager immediately if an estimated and established time set by the farm manager was the same and/or the estimated time ws earlier than the established time and the system detected the delivery.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.11
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• pp.1089-1095
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• 2010

We propose an image segmentation method for auto-teaching system of PCB (Printed Circuit Board) assembly inspection machines. The inspection machine acquires images of all components in PCB, and then compares each image with its standard image to find the assembly errors such as misalignment, inverse polarity, and tombstone. The component window that is the area of component to be acquired by camera, is one of the teaching data for operating the inspection machines. To reduce the teaching time of the machine, we newly develop the image processing method to extract the component window automatically from the image of PCB. The proposed method segments the component window by excluding the soldering parts as well as board background. We binarize the input image by use of HSI color model because it is difficult to discriminate the RGB colors between components and backgrounds. The linear combination of the binarized images then enhances the component window from the background. By use of the horizontal and vertical projection of histogram, we finally obtain the component widow. The experimental results are presented to verify the usefulness of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1103-1109
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• 2014

The motion recognition system has been broadly studied in digital image and video processing fields. Recently, method using th depth image is used very useful. However, recognition accuracy of depth image based method will be loss caused by size and shape of object distorted for angle of the depth sensor. Therefore, distortion correction of depth sensor is positively necessary for distinguished performance of the recognition system. In this paper, we propose a pre-processing algorithm to improve the motion recognition system. Depth data from depth sensor converted to real world, performed the corrected angle, and then inverse converted to projective world. The proposed system make progress using the OpenCV and the window program, and we test a system using the Kinect in real time. In addition, designed using Verilog-HDL and verified through the Zynq-7000 FPGA Board of Xilinx.

• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.676-683
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• 2007

A non-invasive respiratory gated radiotherapy system like those based on external anatomic motion gives better comfortableness to patients than invasive system on treatment. However, higher correlation between the external and internal anatomic motion is required to increase the effectiveness of non-invasive respiratory gated radiotherapy. Both of invasive and non-invasive methods need to track the internal anatomy with the higher precision and rapid response. Especially, the non-invasive method has more difficulty to track the target position successively because of using only image processing. So we developed the system to track the motion for a non-invasive respiratory gated system to accurately find the dynamic position of internal structures such as the diaphragm and tumor. The respiratory organ motion tracking apparatus consists of an image capture board, a fluoroscopy system and a processing computer. After the image board grabs the motion of internal anatomy through the fluoroscopy system, the computer acquires the organ motion tracking data by image processing without any additional physical markers. The patients breathe freely without any forced breath control and coaching, when this experiment was performed. The developed pattern-recognition software could extract the target motion signal in real-time from the acquired fluoroscopic images. The range of mean deviations between the real and acquired target positions was measured for some sample structures in an anatomical model phantom. The mean and max deviation between the real and acquired positions were less than 1mm and 2mm respectively with the standardized movement using a moving stage and an anatomical model phantom. Under the real human body, the mean and maximum distance of the peak to trough was measured 23.5mm and 55.1mm respectively for 13 patients' diaphragm motion. The acquired respiration profile showed that human expiration period was longer than the inspiration period. The above results could be applied to respiratory-gated radiotherapy.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.2
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• pp.45-50
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• 2009

This paper presents an active vision system for on-line traffic sign recognition. The system is composed of two cameras, one is equipped with a wide-angle lens and the other with a telephoto lends, and a PC with an image processing board. The system first detects candidates for traffic signs in the wide-angle image using color, intensity, and shape information. For each candidate, the telephoto-camera is directed to its predicted position to capture the candidate in a large size in the image. The recognition algorithm is designed by intensively using built in functions of an off-the-shelf image processing board to realize both easy implementation and fast recognition. The results of on-road experiments show the feasibility of the system.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.478-481
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• 2005

The PMU (Payload Management Unit) is the main subsystem for the management, control and power supply of the MSC (Multi-Spectral Camera) Payload operation. It is the most important function for the electro-optical camera system that performs the Non-Uniformity Correction (NUC) function of the raw imagery data, rearranges the data from the CCD (Charge Coupled Device) detector and output it to the Data Compression and Storage Unit (DCSU). The NUC board in PMU performs it. In this paper, the NUC board system is described in terms of the configuration and the function, the efficiency for non-uniformity correction, and the influence of the data compression upon the peculiar feature of the CCD pixel. The NUC board is an image-processing unit within the PMU that receives video data from the CEV (Camera Electronic Unit) boards via a hotlinkand performs non-uniformity corrections upon the pixels according to commands received from the SBC (Single Board Computer) in the PMU. The lossy compression in DCSU needs the NUC in on-orbit condition.

• Journal of Korea Multimedia Society
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• v.12 no.3
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• pp.397-408
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• 2009

Image training is a very important yet difficult state for automated visual inspection using computers. Because the size of parts for the recently produced PCB (Printed Circuit Board) becomes smaller and circuit patterns gradually become more complex, a difficult and complex training process is becoming a big problem within an industry where development cycle for new products is short and various products must be inspected. This research produced a reference image by using CAD (Gerber) file which becomes a standard for PCB automatic visual inspection. Reference image from a Gerber file guarantees PCB patterns with no defects. Through system implementation and experimentation, Gerber file is used in order to propose a plan which allows an easy training process for PCB automatic visual inspection system.