• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.113-127
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• 2012

Face detection methods using image processing have been proposed in many different ways. Generally, the most widely used method for face detection is an Adaboost that is proposed by Viola and Jones. This method uses Haar-like feature for image learning, and the detection performance depends on the learned images. It is well performed to detect face images within a certain distance range, but if the image is far away from the camera, face images become so small that may not detect them with the pre-learned Haar-like feature of the face image. In this paper, we propose the far distance face detection method that combine the Aadaboost of Viola-Jones with a saliency map and user's attention information. Saliency Map is used to select the candidate face images in the input image, face images are finally detected among the candidated regions using the Adaboost with Haar-like feature learned in advance. And the user's eye-tracking information is used to select the interest regions. When a subject is so far away from the camera that it is difficult to detect the face image, we expand the small eye gaze spot region using linear interpolation method and reuse that as input image and can increase the face image detection performance. We confirmed the proposed model has better results than the conventional Adaboost in terms of face image detection performance and computational time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.239-246
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• 2005

In this paper. we generate a virtual right image corresponding to the input left image by using given RGB texture data and 8 bit gray scale depth data. We first transform the depth data to disparity data and then produce the virtual right image with this disparity. We also proposed a stereo image synthesis algorithm which is adaptable to a viewer's position and an real-time processing algorithm with a fast LUT(look up table) method. Finally, we could synthesize a total of eleven stereo images with different view points for SD quality of a texture image with 8 bit depth information in a real time.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.41-46
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• 2002

We generally used electric optical sensors in order to detect and identify sea objects efficiently. However due to the limitation of view-angle, the region acquired from the sense is restricted. So it is necessary to generate panoramic image from sea images acquired from pan-tilt camera. Previous mosaicing method is not able to generate panoramic image for sea environment because intensity is similar to all region and time varying. In this paper, we proposed new algorithm for generating high-resolution panoramic image on sea environment. Proposed algorithm use single-view point model, applying mosaicing result in feature environment to in sea environment, we overcame the limitation of previous method. In the result of virtual and real experiment, we showed that proposed algorithm is efficient for generating sea panoramic image.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.209-214
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• 2010

In this paper, We analyzes the image along the platform (Open Eye), through prevention of dementia or stroke patients and cognitive rehabilitation for the proposed system. This way through the camera image according to user's movement gained OpenCV image processing library, which is based on motion analysis, a part of this rehabilitation is to apply to cognitive rehabilitation. Therefore, this paper proposes a new image analysis system has been exposed to the elderly or stroke patients with dementia, their hand gestures through which patients can detect the image of the cognitive rehabilitation to help them in the analysis of the image analysis system is proposed.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.789-792
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• 2003

Pipe inspection has a great importance to ensure safety for the nuclear power plant. In this paper, we designed visual inspection module for the tube internal, which diameter is 15${\sim}$20mm. And we made inspection module which consisted of CCD camera and light. And the relation between image and real world coordinate is established. Image processing is performed to calculate mapping parameter and analyze the size of defect. For the calculation of mapping parameter, experiment is performed using grid type test pattern. Acquired image is processed to extract image coordinate. Edge detection, thresholding, median filtering and morphology filtering is applied to extract grid pattern. Extracted image coordinate is used to calculate image to real world mapping. Lens distortion was considered and corrected to get exact data. Coordinate transformation data is provided for the users to recognize easily. Experiment was performed using grid type test pattern, we extracted lens distortion parameter and real coordinate of defect point. Radial distortion of lens was corrected but tangential distortion was not considered. As continuum to this study, the tangential distortion of lens is considered and improvement of analy zing technique for the tube internal be explored continuously.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.42-42
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• 2017

Prediction of rice yield during a growing season would be very helpful to magnify rice yield as it also allows better farm practices to maximize yield with greater profit and lesser costs. UAV imagery based automatic detection of rice can be a relevant solution for early prediction of yield. So, we propose an image processing technique to predict rice yield using low altitude UAV images. We proposed $L^*a^*b^*$ color space based image segmentation algorithm. All images were captured using UAV mounted RGB camera. The proposed algorithm was developed to find out rice grain area from the image background. We took RGB image and applied filter to remove noise and converted RGB image to $L^*a^*b^*$ color space. All color information contain in both $a^*$ and $b^*$ layers and by using k-mean clustering classification of these colors were executed. Variation between two colors can be measured and labelling of pixels was completed by cluster index. Image was finally segmented using color. The proposed method showed that rice grain could be segmented and we can recognize rice grains from the UAV images. We can analyze grain areas and by estimating area and volume we could predict rice yield.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.3
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• pp.528-533
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• 1997

In the analysis of fatigue crack propagation behavior, the crack length is one of the most important factors. In the test of crack propagation, compliance method is widely used to detect crack length. The measurement of surface crack length is not so easy with compliance method. In this study, the image processing technique was applied to measure the surface crack length. CCD(Charge-coupled device) camera was used to observe the crack image and the computer program to detect crack length from stored crack image was developed. CCT(Center Cracked Tension) specimen was used to compare the compliance method with the image processing technique. The crack length which detected by the image processing techniques was found to be well consistent with that from the optical measurement.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.5
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• pp.135-143
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• 2000

The vision system is easy to use the exclusive use as a independent computer system but it is not much popularization by reason of expensive and difficult to adapt to the various fields, because it is easy to the existed computer system, the price is cheap and also it can use to the various measurement purpose which user wanted and programed. The measurement method of the vehicle axle casing nut welding part is that measure the value of the welding part to adapt the actual operation program from using the ratio between the actual length of the standard specimen and the length of image, to measure the ratio between the actual product and the camera image. A defect is found by the assembled visual inspection system. The inspection algorithm which estimates the quality of welded product is developed and also, the software program which processes the automatic test function of the inspection system. We make the foundation of the inspection automatic system and we will help to apply other welding machine.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.2
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• pp.74-80
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• 2012

In this paper, we developed the profile analysis-based machine vision system for inspecting assembly parts in the industrial field. Implemented system composed of triple set of camera: one was used for acquiring slant image; other is required to acquire a top image; the other was used for side image. After obtaining parts which have gray scale image, threshold value was calculated by analyzing the profile of the image. Experimental results showed that proposed algorithm have a good performance for detecting fault parts and for classifying each parts as well.

• Proceedings of the KSRS Conference
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• v.2
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• pp.631-634
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• 2006

Three main important sources for establishing GIS are the orthomap in scale 1:5 000 with Ground Sampling Distance of 0,5m; DEM/DTM data with height error of ${\pm}$1,0m and topographic map in scale 1: 10 000. The new era with Very High Resolution Satellite (VHRS) images as IKONOS, QuickBird, EROS, OrbView and other ones having Ground Sampling Distance (GSD) even lower than 1m has been in potential for producing orthomap in large scale 1:5 000, to update existing maps, to compile general-purpose or thematic maps and for GIS. The accuracy of orthomap generated from VHRS image affects strongly on GIS reliability. Nevertheless, orthomap accuracy taken from VHRS image is at first dependent on chosen sensor geometrical models. This paper presents, at fist, theoretical basic of the Rational Polynomial Coefficient (RPC) model installed in the commercial ImageStation Systems, realized for orthorectifying VHRS images. The RPC model of VHRS image is a replacement camera mode that represents the indirect relation between terrain and its image acquired on the flight orbit. At the end of this paper the practical accuracies of IKONOS and QuickBird image orthorectified by RPC model on Canadian PCI Geomatica System have been presented. They are important indication for practical application of producing digital orthomaps.