• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.153-156
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• 2003

In this paper, we propose a new scheme for automatic segmentation of the liver in CT images. The proposed scheme is carried out on region of interest(ROI) blocks that include regions of the liver with high probabilities. The ROI approach saves unnecessary computational loss in finding the accurate boundary of the liver. The proposed method utilizes the composition of multi-size morphological filters with a prior knowledge, such as the general location or the approximate intensity of the liver to detect the initial boundary of the liver. Then, we make the gradient image with the weight of the initial liver boundary and segment the liver legion by using an immersion-based waters hed algorithm in the gradient image. finally, the refining process is carried out to acquire a more accurate liver region.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.151-161
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• 2011

PGA(Phase Gradient Autofocus) is a representative autofocus technique to improve the SAR(Synthetic Aperture Radar) image quality. PGA can estimate high order phase errors and have good robustness in noisy environments. However, PGA is not suitable to apply to the stripmap mode data directly because it is based on the spotlight mode operation. In this paper, the PGA implementation technique for stripmap mode data and the method of ROI(Region of Interest) selection that affects severely on PGA performance have been proposed. The proposed technique was verified by the point target simulation first, and was applied to the real SAR signal data acquired by the flight test. Finally, the significant improvements in focusing quality were shown in the processed SAR images using the proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.8
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• pp.45-50
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• 2008

An ink jetting measurement system has been developed such that the velocity as well as the volume of ink droplets can be measured. In order to measure the ink droplet, a strobe LED light was synchronized to the droplet firing signal in order to obtain frozen droplet images. Then, a LabVIEW based software was developed for the analysis of the droplet image. For the efficient droplet analysis, a user generated rectangular shaped ROI (Region of Interest) was used. By using ROI, the ink droplet image can be easily isolated from the other structures such as printhead and the processing area can be minimized.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06d
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• pp.268-271
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• 2008

본 논문에서는 H.264/SVC(Scalability Video Coding)를 기반으로 한 ROI(Region Of Interest) 화질 개선 방법을 제안한다. H.264/SVC는 공간적, 시간적, 화질적 확장성을 지원하고 있다. 이로 인해 네트워크 환경과 모바일 기기에 더욱 적합하게 되었다. 하지만 이러한 확장성은 객관적인 화질 개선을 고려하여 설계되었다. 본 연구는 주관적인 화질 개선을 위해 관심 영역을 설정하였으며, 이를 위하여 관심 영역을 설정하기 위한 방법과 이를 효율적으로 전송하기 위한 효과적인 전송 방법을 제안한다. 또한 기존 SVC 확장성까지도 활용하는 화질 개선 방법을 제시 한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.3
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• pp.249-255
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• 2017

The finger vein recognition technology is a method to acquire a finger vein image by illuminating infrared light to the finger and to authenticate a person through processes such as feature extraction and matching. In order to recognize a finger vein, a 2D mask-based two-dimensional convolution method can be used to detect a finger edge but it takes too much computation time when it is applied to a low cost micro-processor or micro-controller. To solve this problem and improve the recognition rate, this study proposed an extraction method for the region of interest based on virtual core points and moving average filtering based on the threshold and absolute value of difference between pixels without using 2D convolution and 2D masks. To evaluate the performance of the proposed method, 600 finger vein images were used to compare the edge extraction speed and accuracy of ROI extraction between the proposed method and existing methods. The comparison result showed that a processing speed of the proposed method was at least twice faster than those of the existing methods and the accuracy of ROI extraction was 6% higher than those of the existing methods. From the results, the proposed method is expected to have high processing speed and high recognition rate when it is applied to inexpensive microprocessors.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.275-280
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• 2004

In this paper, we propose automatic subtraction radiography algorithms to overcome conventional subtraction radiography's defects by applying image processing technique. In order to reach these goals, this paper suggests the image alignment method that is necessary for getting subtraction image and ROI(Region Of Interest) focused on a selection method using the structure characteristics in target images. Therefore, we use these methods because they give accurary, consistency and objective information or data to results. According to the results, easily and visually we can identify fine difference int the affected parts wether they have problems or not.

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.238-246
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• 2013

In this paper, a robot vision technique is presented to detect obstacles, particularly approaching humans, in the images acquired by a mobile robot that autonomously navigates in a narrow building corridor. A single low-cost color camera is attached to the robot, and a trapezoidal area is set as a region of interest (ROI) in front of the robot in the camera image. The lower parts of a human such as feet and legs are first detected in the ROI from their appearances in real time as the distance between the robot and the human becomes smaller. Then, the human detection is confirmed by detecting his/her face within a small search region specified above the part detected in the trapezoidal ROI. To increase the credibility of detection, a final decision about human detection is made when a face is detected in two consecutive image frames. We tested the proposed method using images of various people in corridor scenes, and could get promising results. This method can be used for a vision-guided mobile robot to make a detour for avoiding collision with a human during its indoor navigation.

• Journal of IKEEE
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• v.16 no.4
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• pp.349-355
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• 2012

Information technology improves convenience, safety, and performance of automobiles. Recently, a lot of algorithms are studied to provide safety and environment information for driving, and lane detection algorithm is one of them. In this paper, we propose a lane detection algorithm that reduces the amount of calculation by reducing region of interest (ROI) after preprocessing. The proposed algorithm reduces the area of ROI a lot by determining the candidate regions near lane boundaries as V-ROI so that the amount of calculation is reduced. In addition, the amount of calculation can be maintained almost the same regardless of the resolutions of the input images by compressing the images since the lane detection algorithm does not require high resolution. The proposed algorithm is implemented using C++ and OpenCV library and is verified to work at 30 fps for realtime operation.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.36-44
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• 2024

This paper presents the application of Convolutional Neural Networks (CNNs) and Region of Interest (ROI) techniques for concrete crack analysis. Surfaces of concrete structures, such as beams, etc., are exposed to fatigue stress and cyclic loads, typically resulting in the initiation of cracks at a microscopic level on the structure's surface. Early detection enables preventative measures to mitigate potential damage and failures. Conventional manual inspections often yield subpar results, especially for large-scale infrastructure where access is challenging and detecting cracks can be difficult. This paper presents data collection, edge segmentation and ROI techniques application, and analysis of concrete cracks using Convolutional Neural Networks. This paper aims to achieve the following objectives: Firstly, achieving improved accuracy in crack detection using image-based technology compared to traditional manual inspection methods. Secondly, developing an algorithm that utilizes enhanced Sobel edge segmentation and ROI techniques. The algorithm provides automated crack detection capabilities for non-destructive testing.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.34-42
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• 2008

This paper proposes the mechanism which improves the qualify of video on a limited network bandwidth by applying the ROI technique to an H.264 Scalable Extension technique. The network environment assumed in this parer is the next generation network convergence environment in which the mobile device has one or more network interfaces. Therefore, we allocate the priority to video packets as the hierarchy structure of H.264 SVC-encoded video stream and ROI information, and transmit those packets over appropriate network channel for using those multiple network interfaces. This paper shows two experiments first one is extracting and allocating the video stream on an appropriate network channel, second one is unequal packet transmission by allocated priorities (e.g. ROI). Performance evaluations show that this approach delivers an improved decoded video quality when compared with conventional transmission schemes, especially on device which has multiple network interfaces.