• Proceedings of the PSK Conference
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• 2001.10a
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• pp.225.1-225.1
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• 2001

• Genomics & Informatics
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• v.19 no.3
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• pp.20.1-20.2
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• 2021

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.10
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• pp.909-919
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• 2014

License plate (LP) detection is the most imperative part of an automatic LP recognition (LPR) system. Typical LPR contains two steps, namely LP detection (LPD) and character recognition. In this paper, we propose an efficient Vehicle-to-LP detection framework which combines with an adaptive GMM (Gaussian Mixture Model) and a cascade of boosted classifiers to make a faster vehicle LP detector. To develop a background model by using a GMM is possible in the circumstance of a fixed camera and extracts the motions using background subtraction. Firstly, an adaptive GMM is used to find the region of interest (ROI) on which motion detectors are running to detect the vehicle area as blobs ROIs. Secondly, a cascade of boosted classifiers is executed on the blobs ROIs to detect a LP. The experimental results on our test video with the resolution of $720{\times}576$ show that the LPD rate of the proposed system is 99.14% and the average computational time is approximately 42ms.

• Journal of the HCI Society of Korea
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• v.2 no.1
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• pp.1-12
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• 2007

In this paper, we propose a video service system that reflects user interaction in the multimedia contents to increase user satisfaction in the restricted content consumption environment. The proposed system is based on the multiple ROI(Region of Interest) coding in H.264/AVC Scalable Video Coding (SVC). The proposed system provides scalable video quality by adopting SVC. And by bidirectional communication between user and video server, it enables user to select meaningful ROI among multiple ROIs by user interaction. To verify the usefulness of the proposed system, we demonstrate it with a test-bed on which user interactive ROIs are implemented.

• Imaging Science in Dentistry
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• v.35 no.3
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• pp.141-146
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• 2005

Purpose : The purpose of this study was to investigate the preliminary use of morphologic operation (MO) in analyzing trabecular pattern of alveolar bone for the predicting systemic osteoporosis. Materials and Methods : Study subjects consisted of 35 females (average age 48.5 years) and 25 males (average age 25.8 years). Bone mineral density BMD $(grams/cm^2)$ of lumbar spine and proximal femur of these subjects were measured by a dual energy X-ray absorptiometry (DEXA). Regions of interest (ROIs) were selected from the digitized periapical radiographs of subjects' posterior jaw. A custom computer program processed morphology operations of ROIs. We compared mean values of 11 MO variables according to the osteoporotic group divided by the T-scores of DEXA. We also studied correlation between radiographic density and these MO variables. Results : The mean radiographic densities insignificantly correlated with MO variables. There were statistically significant differences among the values of 9 MO variables according to the osteoporotic group. Conclusion Morphologic operation can be effective in analyzing trabecular pattern of alveolar bone for the predicting osteoporosis.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.87-96
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• 2018

In this paper, we propose a method to determine whether there is a defect by using the similarity between ROIs (Region of Interest) of the standard image and ROIs of the image which is corrected in position and rotation after capturing the vehicle headlight. The degree of similarity is determined by the template matching based on the histogram of image, which is a some modification of the method provided by OpenCV where template matching is performed on the raw image not the histogram. The proposed method is compared with the basic method of OpenCV for performance analysis. As a result of the analysis, it was found that the proposed method showed better performance than the OpenCV method, showing the accuracy close to 100%.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.5
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• pp.314-318
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• 2010

This paper proposes an image retrieval method based on the Multiple Region-of-Interest. In the proposed method, the image is segmented into blocks, among which the blocks overlapped with multiple ROIs are selected. The similarity of images is measured using the MPEG-7 dominant color descriptor(DCD) and considering the relative location of the overlapped blocks. The experimental results showed that the proposed method improves the retrieval performance than the previous methods using the global DCD or comparing the blocks at the same position. In addition, the method that considers the relative position of blocks overlapped with the multiple ROIs also showed a better performance than the existing methods.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.4
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• pp.169-178
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• 2018

Currently, various sensors have been used for advanced driver assistance systems. In order to overcome the limitations of individual sensors, sensor fusion has recently attracted the attention in the field of intelligence vehicles. Thus, vision and radar based sensor fusion has become a popular concept. The typical method of sensor fusion involves vision sensor that recognizes targets based on ROIs (Regions Of Interest) generated by radar sensors. Especially, because AVM (Around View Monitor) cameras due to their wide-angle lenses have limitations of detection performance over near distance and around the edges of the angle of view, for high performance of sensor fusion using AVM cameras and radar sensors the exact ROI extraction of the radar sensor is very important. In order to resolve this problem, we proposed a sensor fusion scheme based on commercial radar modules of the vendor Delphi. First, we configured multiple radar data logging systems together with AVM cameras. We also designed radar post-processing algorithms to extract the exact ROIs. Finally, using the developed hardware and software platforms, we verified the post-data processing algorithm under indoor and outdoor environments.

• The Journal of Korean Physical Therapy
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• v.27 no.3
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• pp.135-139
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• 2015

Purpose: The aim of this study was to compare EEG topographical maps in patients with chronic stroke after action observation physical training. Methods: Ten subjects were recruited from a medical hospital. Participants observed the action of transferring a small block from one box to another for 6 sessions of 1 minute each, and then performed the observed action for 3 minutes, 6 times. An EEG-based brain mapping system with 32 scalp sites was used to determine cortical reorganization in the regions of interest (ROIs) during observation of movement. The EEG-based brain mapping was comparison in within-group before and after training. ROIs included the primary sensorimotor cortex, premotor cortex, superior parietal lobule, inferior parietal lobule, superior temporal lobe, and visual cortex. EEG data were analyzed with an average log ratio in order to control the variability of the absolute mu power. The mu power log ratio was in within-group comparison with paired t-tests. Results: Participants showed activation prior to the intervention in all of the cerebral cortex, whereas the inferior frontal gyrus, superior frontal gyrus, precentral gyrus, and inferior parietal cortex were selectively activated after the training. There were no differences in mu power between each session. Conclusion: These findings suggest that action observation physical training contributes to attaining brain reorganization and improving brain functionality, as part of rehabilitation and intervention programs.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.99-106
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• 2007

In this paper, we present an AAW(Adaptive Attention Window) based cell image segmentation method. For semantic AAW detection we create an initial Attention Window by using a luminance map. Then the initial AW is reduced to the optimal size of the real ROI(Region of Interest) by using a quad tree segmentation. The purpose of AAW is to remove the background and to reduce the amount of processing time for segmenting ROIs. Experimental results show that the proposed method segments one or more ROIs efficiently and gives the similar segmentation result as compared with the human perception.