• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.123-134
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• 2008

In this paper, we propose a real-tin e face recognition system that is robust under various lighting conditions. Th Modified Census Transform algorithm that is insensitive to illumination variations is employed to extract local structure features. In a practical face recognition system, acquired images through a camera are likely to be blurred and some of them could be side face images, resulting that unacceptable performance could be obtained. To improve stability of a practical face recognition system, we propose a real-time algorithm that rejects unnecessary facial picture and makes use of recognition consistency between successive frames. Experimental results on the Yale database with large illumination variations show that the proposed approach is approximately 20% better than conventional appearance-based approaches. We also found that the proposed real-time method is more stable than existing methods that produces recognition result for each frame.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.701-708
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• 2004

Existing contents-based video retrieval systems search by using a single method such as annotation-based or feature-based retrieval. Hence, it not only shows low search efficiency, but also requires many efforts to provide system administrator or annotator with a perfect automatic processing. Tn this paper, we propose an agent-based, and automatic and unified semantics-based video retrieval system, which support various semantics-retrieval of the massive video data by integrating the feature-based retrieval and the annotation-based retrieval. The indexing agent embodies the semantics about annotation of extracted key frames by analyzing a fundamental query of a user and by selecting a key-frame image that is ed by a query. Also, a key frame selected by user takes a query image of the feature-based retrieval and the indexing agent searches and displays the most similar key-frame images after comparing query images with key frames in the database by using the color-multiple-partition histogram techniques. Furthermore, it is shown that the performance of the proposed system can be significantly improved.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.137-138
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• 2008

This paper proposes the modified image contrast enhancement technique for small-sized display of mobile handset. Sample images are user interface images, in which scaled up wVGA($800{\times}480$) from qVGA($320{\times}240$) that we can see easily in mobile handset. The display size of mobile handset is relatively small, so the goal of this paper is to simplify image contrast enhancement algorithm based on conventional HE (Histogram Equalization) algorithm and improve computational effectiveness to minimize power consumption in real hardware IC. In this paper, we adopt HE technique, which is classical and widely used for image contrast enhancement. At first, the input frame image is partitioned to temporal sub-frames and then analyzes gray level histogram of each sub-frame. In case that the analyzed histogram of some sub-frames deviates so much from reference level (it means that the sub-frame image components consist of too bright ones or dark ones), apply DHE(Dynamic Histogram Equalization) algorithm. In the other case, apply classical Histogram Linearization (or Global HE) algorithm. Also we compare the HE technique with gamma LUT (Look-Up Table) method, which is known as the simplest technique to enhance image contrast.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.4
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• pp.81-88
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• 2007

The geometry of satellite image captured by linear CCD sensor is different from that of frame camera image. The fact that the exterior orientation parameters for satellite image with linear CCD sensor varies from scan line by scan line, causes the difference of image geometry between frame and linear CCD sensor. Therefore, we need the epipolar geometry for linear CCD image which differs from that of frame camera image. In this paper, we proposed a method of resampling linear CCD satellite image in epipolar geometry under the assumption that image is not formed in perspective projection but in parallel projection, and the sensor model is a 2D affine sensor model based on parallel projection. For the experiment, IKONOS stereo images, which are high resolution linear CCD images, were used and tested. As results, the spatial accuracy of 2D affine sensor model is investigated and the accuracy of epipolar resampled image with RFM was presented.

• Journal of Broadcast Engineering
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• v.2 no.1
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• pp.56-64
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• 1997

An HDTV frame has 4~6 times more pixels than a DTV frame. In order to encode the HDTV image in real time, parallel processing architectures have been widely used in many HDTV codec developments. That is, an HDTV Image is divided into several subbands and each subband is encoded in parallel using some DTV level encoders. In this paper, we adopt an HDTV codec architecture which divides an HDTV frame into 4 subbands and propose a new scene change detection algorithm using local variance. In addition, a new adaptive multichannel rate control scheme which allocate target bits adaptively to each subband of the HDTV image based on the activities of subband images is suggested in this paper. The activities of subband images are calculated at scene change detection part and reused at the adaptive rate control part. The simulation results show that the proposed scene change detection algorithm detects the scene change of HDTV video very accurately. Also the suggested adaptive multichannel rate control scheme shows better performance than the rate control method which allocates target bits equally to each subbands of the HDTV image.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.33-45
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• 2011

In this paper, we present a method for extracting video objects efficiently by using the modified graph cut algorithm based on contour information. First, we extract objects at the first frame by an automatic object extraction algorithm or the user interaction. To estimate the objects' contours at the current frame, motion information of objects' contour in the previous frame is analyzed. Block-based histogram back-projection is conducted along the estimated contour point. Each color model of objects and background can be generated from back-projection images. The probabilities of links between neighboring pixels are decided by the logarithmic based distance transform map obtained from the estimated contour image. Energy of the graph is defined by predefined color models and logarithmic distance transform map. Finally, the object is extracted by minimizing the energy. Experimental results of various test images show that our algorithm works more accurately than other methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.99-107
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• 2014

In this paper, a landmark based localization system using a Kinect sensor is proposed and evaluated with the implemented system for precise and autonomous navigation of low cost robots. The proposed localization method finds the positions of landmark on the image plane and the depth value using color and depth images. The coordinates transforms are defined using the depth value. Using coordinate transformation, the position in the image plane is transformed to the position in the body frame. The ranges between the landmarks and the Kinect sensor are the norm of the landmark positions in body frame. The Kinect sensor position is computed using the tri-lateral whose inputs are the ranges and the known landmark positions. In addition, a new matching method using the pin hole model is proposed to reduce the mismatch between depth and color images. Furthermore, a height error compensation method using the relationship between the body frame and real world coordinates is proposed to reduce the effect of wrong leveling. The error analysis are also given to find out the effect of focal length, principal point and depth value to the range. The experiments using 2D bar code with the implemented system show that the position with less than 3cm error is obtained in enclosed space($3,500mm{\times}3,000mm{\times}2,500mm$).

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.337-344
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• 2002

In general, in order to obtain position information from satellite images, satellite sensor model which represents the geometric relationship between sensor and targeted area should be established in the first place. However, it is not simple for modelling pushbroom satellite sensor due to the image capturing process. In recent development of new generation imaging sensors, a generic sensor model, which is applicable to all types of sensors such as frame, pushbroom, whiskbroom, and SAR is in great need to the remote sensing and photogrammetry community. In this paper, the RFM as sensor model was implemented with KOMPSAT EOC and SPOT satellite images and analyzed in cases where the number and distribution of ground control points were varied. The test results of RFM were presented and compared with those of Direct Linear Transformation(DLT).

• The Journal of Korean Institute of Information Technology
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• v.17 no.8
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• pp.1-9
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• 2019

With the development of imaging information communication technology in modern society, imaging acquisition and mass production technology have developed rapidly. However, crime rates using these technology are increased and forensic studies are conducted to prevent it. Identification techniques for image acquisition devices are studied a lot, but the field is limited to images. In this paper, camera model identification technique for video, not image is proposed. We analyzed video frames using the trained model with images. Through training and analysis by considering the frame characteristics of video, we showed the superiority of the model using the P frame. Then, we presented a video camera model identification system by applying a majority-based decision algorithm. In the experiment using 5 video camera models, we obtained maximum 96.18% accuracy for each frame identification and the proposed video camera model identification system achieved 100% identification rate for each camera model.

• Journal of the Korean Wood Science and Technology
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• v.40 no.5
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• pp.319-326
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• 2012

Han-green building is one of the modernized Korean traditional buildings developed by Korea Forest Research Institute. This building was developed to increase the competitiveness of Korean traditional building using state-of-art technologies; hence Han-green building has the inherent characteristics of traditional building such as exposed wood frame in wall. Because of discontinuity in wall by the exposed wood frame, there is a concern on heat-air leaking in terms of energy performance. In this study, air-tightness of Han-green building was evaluated to investigate the influence of gaps between frames and in-fill walls. Blower door test was carried out to evaluate the air-tightness, and air-change rate (ACH50) was evaluated by averaging four set of pressurization and depressurization test. The air-change rate of Han-green house was 5.91 $h^{-1}$. To improve energy performance of Han-green house, thermal infrared images of Han-green house were taken in winter with heating to find out where the heat loss occurred. It was found that the building lost more heat through gaps between frames and in-fill walls rather than through other parts of this building. After covering all the gaps by taping, the blower door test was performed again, and the air-change rate was improved to 5.25 $h^{-1}$. From this analysis, it was concluded that the heated air can leak through the gaps between frames and walls. Therefore, when one designs the post and beam building with exposed frame, the detail design between frame and wall needs to be carefully dealt. However, Han-green building showed relatively high air-tightness comparing with other country research results.