• Journal of IKEEE
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• v.18 no.4
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• pp.581-585
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• 2014

In this paper, we propose a pedestrian detection by applying the HOG feature using ROI. Conventional HOG method has high accuracy, but shows the disadvantage of slow processing speed. By applying the ROI to the conventional method reduce computations for unnecessary area. Therefore proposed method improves the processing speed. In order to set the ROI area, we propose a structure that combined odd frames and even frames. Odd frame is in charge of operation for the entire area. And even frame does the operation for the ROI area. Implementation results of proposed method maintaining the same accuracy as the conventional method show a 20% improved performance of 8.3 frames per second.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.31-39
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• 2010

In some image processing system or the users who want to see a specific region of image simply, if a part of the image has higher quality than other regions, it would be a nice service. Specifically in mobile environments, preferential service was needed, as the screen size is small. So, JPEG2000 supplies this function. But this doesn't support the process to extract specific regions or service and does the functions to add some techniques. It is called by ROI(Region-of-Interest). In this paper, we use images including human faces, which are processed most preferentially and compressed with high quality. Before an image is served to the users, it is compressed and saved. Here, the face parts are compressed with higher quality than the background which are relatively with lower quality. This technique can offer better service with preferential transferring of the faces, too. Besides, whole regions of the image are compressed with same quality and after searching the faces, they can be preferentially transferred. In this paper, we use a face extraction approach based on neural network and the preferential processing with EBCOT of JPEG2000. For experimentation, we use images having several human faces and evaluate objectively and subjectively, and proved that this approach is a nice one.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.73-80
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• 2004

In this paper, we propose a medical image processing method for detection of periodontal disease. The proposed method is the method of an automatic image alignment and detection of minute changes, to overcome defects in the conventional subtraction radiography by digital image processing technique, that is necessary for getting subtraction image and ROI(Region of Interest) focused on a selection method using the structured features in target images. And the method services accuracy, consistency and objective information or data to results. In result, easily and visually we can identify minute differences in the affected parts whether they have problems or not, and using application system.

• Journal of Korea Multimedia Society
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• v.18 no.1
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• pp.1-8
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• 2015

In recent years, ear has emerged as a new biometric trait, because it has advantage of higher user acceptance than fingerprint and can be captured at remote distance in an indoor or outdoor environment. This paper proposes an individual identification method using ear region based on SIFT(shift invariant feature transform). Unlike most of the previous studies using rectangle shape for extracting a region of interest(ROI), this study sets an ROI as a flexible expanded region including ear. It also presents an effective extraction and matching method for SIFT keypoints. Experiments for evaluating the performance of the proposed method were performed on IITD public database. It showed correct identification rate of 98.89%, and it showed 98.44% with a deformed dataset of 20% occlusion. These results show that the proposed method is effective in ear recognition and robust to occlusion.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.222-224
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• 2009

This paper presents an algorithm that extracts road lane's specific information by using HSI color information and performance enhancement of lane detection base on vision processing of drive assist. As a preprocessing for high speed lane detection, the optimal extraction of region of interest for lane boundary(ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled and it also increases reliabilities by deleting edges those are misrecognized. Road lane is extracted with simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since noise can be removed by using saturation and brightness of HSI color model. Also it searches for the road lane's color information and extracts characteristics. The real road experimental results are presented to evaluate the effectiveness of the proposed method.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.87-96
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• 2005

In this paper, a selective visual attention module based on motion stimuli is introduced for the purpose of detecting ROI(region of interest) or FOA(focus of attention) in motion pictures. Analysis of motion fields in our approach is in direct contrast to some of the previous studies of selective visual attention module. Motion that presents temporal visual saliency in an aspect between two successive frames is analyzed based on psychological studies in 'DORF(double opponent receptive fields)' and 'NF(noise filtration)' in MT(middle temporal cortex). Analyzed results are integrated based on the theory of 'motion integration' in MT to obtain a single conspicuous region. Experiments through a human subjective evaluation showed generally accepted results.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.197-206
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• 2006

One of the most significant characteristics of JPEG2000. the emerging still image standards. is the ROI (Region of Interest) coding. JPEG2000 provides a number of ROI coding mechanisms and ROI parameters. To apply them to an application, it must select the applicable values. In this paper, we evaluate how the ROI coding mechanisms and the ROI parameters influencing JPEG2000 qualify affect the ROI quality and the whole image quality. The ROI coding mechanisms are Maxshift and Implicit. and the parameters are tile size and ROI size, codeblock size, number of DWT decomposition levels and ROI importance. The bigger the tile size, the better the quality. The bigger the ROI size, the ROI importance and the number of DWT decomposition levels, the worse the qualify. In code block $32{\times}32$ of Maxshift and Implicit, it has the best qualify.

• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.310-319
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• 2016

This paper proposes an effective FRUC (Frame Rate Up-Conversion) technique, which is based on ROI (Region Of Interest) separations and adaptive motion vector refinement. In this paper, in order to overcome the weakness of the EBME (Extended Bi-lateral Motion Estimation) algorithm, which is widely known in FRUC techniques, first, the proposed algorithm performs a bi-directional motion estimation for the complementary asymmetric region. Then, the proposed algorithm classifies each block into ROI or non-ROI block and refine motion vectors in accordance with their block characteristics to have a higher accuracy than the conventional EBME algorithm, specially, for the occlusion regions. The experimental results show that the proposed algorithm can improves 0.59dB on average PSNR as compared to the conventional method.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.983-991
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• 2019

This study aims to analyze movies which contain various stories according to the size of their shots. To achieve this, it is needed to classify dataset according to the shot size, such as extreme close-up shots, close-up shots, medium shots, full shots, and long shots. However, a typical video storytelling is mainly composed of close-up shots, medium shots, full shots, and long shots, it is not an easy task to construct an appropriate dataset for extreme close-up shots. To solve this, we propose an image cropping method based on the region of interest (ROI) detection. In this paper, we use the face detection and saliency detection to estimate the ROI. By cropping the ROI of close-up images, we generate extreme close-up images. The dataset which is enriched by proposed method is utilized to construct a model for classifying shots based on its size. The study can help to analyze the emotional changes of characters in video stories and to predict how the composition of the story changes over time. If AI is used more actively in the future in entertainment fields, it is expected to affect the automatic adjustment and creation of characters, dialogue, and image editing.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.3
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• pp.246-253
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• 2003

The initiation and growth of short fatigue cracks in the simulated aircraft structure with a series of rivet holes was detected by acoustic emission (AE). The location and the size of short tracks were determined by AE source location techniques and the measurement with traveling microscope. AE events increased intermittently with the initiation and growth of short cracks to form a stepwise increment curve of cumulative AE events. For the precise determination of AE source locations, a region-of-interest (ROI) was set around the rivet holes based on the plastic zone size in fracture mechanics. Since the signal-to-noise ratio (SNR) was very low at this early stage of fatigue cracks, the accuracy of source location was also enhanced by the wavelet transform do-noising. In practice, the majority of AE signals detected within the ROI appeared to be noise from various origins. The results showed that the effort of structural geometry and SNR should be closely taken into consideration for the accurate evaluation of fatigue damage in the structure.