• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.439-442
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• 1990

A powerful general purpose image processing processor is developed using a high-speed DSP chip, TMS320C30. The image processing processor, compatible to the standard VME bus, is composed of VME bus interface unit, video rate image grabbing/coding unit, TMS320C30 interface unit and bank of high-speed SRAMs. The performance is evaluated experimentally with the general image processing algorithms and the results show that the developed processor is capable of high speed image processing.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.634-636
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• 2003

Satrec Initiative (Si) is developing a ground processing system for Synthetic Aperture Radar (SAR) data. SAR provides its own illumination and is not dependent on the light from sun, thus permitting continuous day/night operation and all-weather imaging. The system is capable of producing standard level products from SAR signal. Hence, the system should be able to perform matched filtering, range compression, azimuth compression, multi-look image generation, and geocoded image generation. This paper will describe the processing steps including algorithms, design, and accuracy of the Si's SAR processing system by comparing with commercial software.

• Journal of the Semiconductor & Display Technology
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• v.9 no.3
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• pp.59-63
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• 2010

This paper proposes computer visual inspection algorithms for various LCD defects which are found in a manufacturing process. Modular vision processing steps are required in order to detect different types of LCD defects. Those key modules include RGB filtering for pixel defects, gray-scale morphological processing and Hough transform for line defects, and adaptive threshold for spot defects. The proposed algorithms can give users detailed information on the type of defects in the LCD panel, the size of defect, and its location. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.773-779
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• 1996

Dried oak mushroom have complex and various visual features. Grading and sorting of dried oak mushrooms has been done by the human expert. Though actions involved in human grading looked simple, a decision making underneath the simple action comes from the result of the complex neural processing of the visual image. Through processing details involved in human visual recognition has not been fully investigated yet, it might say human can recognize objects via one of three ways such as extracting specific features or just image itself without extracting those features or in a combined manner. In most cases, extracting some special quantitative features from the camera image requires complex algorithms and processing of the gray level image requires the heavy computing load. This fact can be worse especially in dealing with nonuniform, irregular and fuzzy shaped agricultural products, resulting in poor performance because of the sensitiveness to the crisp criteria or specific ules set up by algorithms. Also restriction of the real time processing often forces to use binary segmentation but in that case some important information of the object can be lost. In this paper, the neuro net based real time recognition algorithm was proposed without extracting any visual feature but using only the directly captured raw gray images. Specially formated adaptable size of grids was proposed for the network input. The compensation of illumination was also done to accomodate the variable lighting environment. The proposed grading scheme showed very successful results.

• The Journal of Korea Robotics Society
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• v.10 no.3
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• pp.146-153
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• 2015

In order to contain as much information as possible in a single image, a wide FOV(Field-Of-View) imaging system is required. The catadioptric imaging system with hyperbolic cylinder mirror can acquire over 180 degree horizontal FOV realtime panorama image by using a conventional camera. Because the hyperbolic cylinder mirror has a curved surface in horizontal axis, the original image acquired from the imaging system has the geometrical distortion, which requires the image processing algorithm for reconstruction. In this paper, the image reconstruction algorithms for two cases are studied: (1) to obtain an image with uniform angular resolution and (2) to obtain horizontally rectilinear image. The image acquisition model of the hyperbolic cylinder mirror imaging system is analyzed by the geometrical optics and the image reconstruction algorithms are proposed based on the image acquisition model. To show the validity of the proposed algorithms, experiments are carried out and presented in this paper. The experimental results show that the reconstructed images have a uniform angular resolution and a rectilinear form in horizontal axis, which are natural to human.

• Journal of the Optical Society of Korea
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• v.14 no.2
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• pp.109-120
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• 2010

We have developed mathematically precise image-processing algorithms for extracting rectilinear images from fisheye images as well as digital pan/tilt/zoom technology. Using this technology, vertical lines always appear as vertical lines in the panned and/or tilted images. Furthermore, polygonal panoramic images composed of multiple rectilinear images have been obtained using the developed digital pan/tilt technology.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.260-264
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• 1987

Algorithms to detect in real-time both position and orientation of rectangular type electronic components are developed for industrial vision. In order to conduct detection in real-time, parallel processing algorithm of image date which uses several control processor is proposed. Image processing area is divided into several regions which can be processed by each cpu. As a result, processing time is improved when two control processors are used and real-time pattern recognition of not-well-aligned components is accomplished.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.87-91
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• 2022

Bokeh effect is a stylistic technique that can produce blurring the background of photos. This paper implements to produce a bokeh effect with a single image by post processing. Generating depth map is a key process of bokeh effect, and depth map is an image that contains information relating to the distance of the surfaces of scene objects from a viewpoint. First, this work presents algorithms to determine the depth map from a single input image. Then, we obtain a sparse defocus map with gradient ratio from input image and blurred image. Defocus map is obtained by propagating threshold values from edges using matting Laplacian. Finally, we obtain the blurred image on foreground and background segmentation with bokeh effect achieved. With the experimental results, an efficient image processing method with bokeh effect applied using a single image is presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1828-1836
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• 2015

Object tracking algorithms can reduce computational cost by avoiding computation over the whole image through the selection of region of interests based on object detection. So, accurate object detection is an important task for object tracking. The background subtraction algorithm has been widely used in moving object detection using a stationary camera. However, it has the problem of object detection error due to incorrect background modeling, whereas the method of background modeling has been improved by many researches. This paper proposes a new moving object detection algorithm to overcome the drawback of the conventional background subtraction algorithm by combining the background subtraction algorithm with the motion history image algorithm that is usually used in gesture detection. Although the proposed algorithm demands more processing time because of time taken for combining two algorithms, it meet the real-time processing requirement. Moreover, experimental results show that it has higher accuracy compared with the previous two algorithms.

• Journal of Welding and Joining
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• v.34 no.2
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• pp.59-66
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• 2016

The Gas Metal Arc(GMA) welding, called Metal Inert Gas(MIG) welding, has been an important component in manufacturing industries. A key technology for robotic welding processes is seam tracking system, which is critical to improve the welding quality and welding capacities. The objectives of this study were to develop the intelligent and cost-effective algorithms for image processing in GMA welding which based on the laser vision sensor. Welding images were captured from the CCD camera and then processed by the proposed algorithm to track the weld joint location. The proposed algorithms that commonly used at the present stage were verified and compared to obtain the optimal one for each step in image processing. Finally, validity of the proposed algorithms was examined by using weld seam images obtained with different welding environments for image processing. The results proved that the proposed algorithm was quite excellent in getting rid of the variable noises to extract the feature points and centerline for seam tracking in GMA welding and could be employed for general industrial application.