• Journal of the Korean Society for Precision Engineering
• /
• v.21 no.11
• /
• pp.200-208
• /
• 2004

In ultrasonic bone densitometry, the positioning of measurement site is decisive in precision and reproducibility. In this study, automatic Region of Interest (ROI) detection algorithm is suggested and adopted the method using the local minimum value by ultrasonic image. The preprocess before the local minimum method extracts out the bone area and calculates the geometrical information of bone. The developed ROI detection algorithm was applied to the clinical test for the subject of 305 female patients in the range of 22-88 years old. As the results, the accuracy of the algorithm was shown to be 98.3％. It was also found that bone density parameter was significantly correlated with age(r=0.85, p<0.0001).

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.3
• /
• pp.577-583
• /
• 2007

The character strings on chips and components are so tiny and numerous that it is a very difficult work for people to perform. In this paper, we propose a mark automatic checking system, which will determine whether chip is wrong-mark or not by recognizing characters on chips. Lots of faulty detection conditions and template matching methods are used to inspect the faulty mark items. The faulty detection classifies conditions as five kinds-darkness, matching, area, broken and branch. A series of experimentation show that the method proposed here can offer an effective way to determine wrong-mark on chips.

• Journal of Digital Contents Society
• /
• v.12 no.1
• /
• pp.1-9
• /
• 2011

JPEG2000 offers the technique which compresses the interested regions with higher quality than the background. It is called by an ROI(Region-of-Interest) coding method. In this paper, we use images including the human faces, which are processed uppermost and compressed with high quality. The proposed method consists of 2 steps. The first step extracts some faces and the second one is ROI coding. To extract the faces, the method cuts or scale-downs some regions with $20{\times}20$ window pixels for all the pixels of the image, and after preprocessing, recognizes the faces using neural networks. Each extracted region is identified by ROI mask and then ROI-coded using Maxshift method. After then, the image is compressed and saved using EBCOT. The existing methods searched the ROI by edge distributions. On the contrary, the proposed method uses human intellect. And the experiment shows that the method is sufficiently useful with images having several human faces.

• Journal of the Korean Society of Radiology
• /
• v.17 no.5
• /
• pp.685-691
• /
• 2023

This study aims to raise awareness of the exposure index according to the Sub-ROI in clinical use by studying the effect of Sub-ROI's change on exposure index and dose during Chest PA examination. In this study, to examine the changes in EI and ESD according to the Sub-ROI setting, the irradiation conditions were set to 120 kVp, 200 mA, 2 mAs, and the SID was fixed to 180cm. Five types of Sub-ROI were used. The average value of EI according to the Sub-ROI's change was 135.58 ± 0.89 in AEC, 100.80 ± 0.80 in VR, 143.43 ± 0.76 in HR, 103.22 ± 0.68 in LS, and 102.79 ± 0.84 in SS. The mean value of ESD was 30.28±0.50 µGy in AEC, 30.16 ± 0.44 µGy in VR, 30.30 ± 0.46 µGy in HR, 30.23 ± 0.46 µGy in LS, and 30.28 ± 0.51 µGy in SS. As a result of this study, based on the AEC mode recommended by the manufacturer, the VR (25.7%), LS (23.9%), and SS (24.2%) modes decreased, and the HR mode increased by 5.7%. However, ESD was not affected by the Sub-ROI's change. Therefore, Sub-ROI may change EI during the Chest PA examination, it is considered that Sub-ROI should be used appropriately when setting protocols in clinical use.

• Journal of Korea Multimedia Society
• /
• v.15 no.6
• /
• pp.737-747
• /
• 2012

Recently, in order to support automatic meter reading for conventional metering devices, an image processing-based approach of recognizing the number meter data in the captured meter images has attracted many researchers' interests. Numerical character segmentation is a very critical process for successful recognition. In this paper, we propose an efficient numeric character segmentation method which can segment numeric characters well for any metering device types under diverse illumination environments. The proposed method consists of two consecutive stages; detection of number area containing all numbers as a tight ROI(Region of Interest) and segmentation of numerical characters in the ROI. Detection of tight ROI is achieved in two steps: extraction of rough ROI by utilizing horizontal line segments after illumination enhancement preprocessing, and making the rough ROI more tight through clipping utilizing vertical and horizontal projection about binarized ROI. Numerical character segmentation in the detected ROI is stably achieved in two processes of 'vertical segmentation of each number region' and 'number segmentation in the each vertical segmented number region'. Through the experiments about a homegrown meter image database containing various meter type images of low contrast, low intensity, shadow, and saturation, it is shown that the proposed numeric character segmentation method performs effectively well for any metering device types under diverse illumination environments.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.11a
• /
• pp.842-844
• /
• 2017

본 연구는 뷔페형 카페테리아 식당에서 근무하는 직원들이 계산 업무를 덜고 조리 업무에 집중하여 업무 성과, 직무만족도를 높일 수 있도록 돕는 카페테리아 무인계산시스템을 제안한다. 무인계산시스템의 작동과정은 크게 두 가지이다. 첫째, 식판을 가져오면 그 위의 음식들을 촬영하여 음식 부분의 ROI(Region of Interest, ROI) 이미지를 추출해낸다. 둘째, 미리 학습된 모델에 앞서 추출한 ROI 이미지를 입력하여 식판 위에 어떤 이미지들이 있는지 분석한다. 그 후 해당 음식과 가격을 GUI로 출력하여 사용자가 확인 후 결제할 수 있도록 한다.

• Journal of Information Processing Systems
• /
• v.13 no.1
• /
• pp.40-56
• /
• 2017

Since the progress of digital medical imaging techniques, it has been needed to compress the variety of medical images. In medical imaging, reversible compression of image's region of interest (ROI) which is diagnostically relevant is considered essential. Then, improving the global compression rate of the image can also be obtained by separately coding the ROI part and the remaining image (called background). For this purpose, the present work proposes an efficient reversible discrete cosine transform (RDCT) based embedded image coder designed for lossless ROI coding in very high compression ratio. Motivated by the wavelet structure of DCT, the proposed rearranged structure is well coupled with a lossless embedded zerotree wavelet coder (LEZW), while the background is highly compressed using the set partitioning in hierarchical trees (SPIHT) technique. Results coding shows that the performance of the proposed new coder is much superior to that of various state-of-art still image compression methods.

• Journal of Sensor Science and Technology
• /
• v.12 no.3
• /
• pp.128-138
• /
• 2003

In this paper, we proposed the algorithm for locating destination address block (DAB) from automatic system to classify packages. For locating DAB, because the size of obtained images is are very large, we select the region of interesting (ROI) to reduce time carrying into algorithm. After selecting the ROI, proposed algorithm is carried out within the ROI. We extract the outline of the handwriting part of the DAB and the rest components within the obtained ROI using thresholding. We carry out labeling to extract each connected component for extracted outline and the rest components. We extract the outline of the handwriting part of the DAB using the geometrical characteristic of the outline of the handwriting part of the DAB among many connected components. The last, we extract the locating DAB using the outline of the handwriting part of the DAB.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.3
• /
• pp.93-101
• /
• 2009

This paper suggests a new algorithm automatically searching for Region-of-Interest(ROI) with high speed, using the edge information of high frequency subband transformed with wavelet. The proposed method executes a searching algorithm of 4-direction object boundary by the unit of block using the edge information, and detects ROIs. The whole image is splitted by $64{\times}64$ or $32{\times}32$ sized blocks and the blocks can be ROI block or background block according to taking the edges or not. The 4-directions searche the image from the outside to the center and the algorithm uses a feature that the low-DOF image has some edges as one goes to center. After searching all the edges, the method regards the inner blocks of the edges as ROI, and makes the ROI masks and sends them to server. This is one of the dynamic ROI method. The existing methods have had some problems of complicated filtering and region merge, but this method improved considerably the problems. Also, it was possible to apply to an application requiring real-time processing caused by the process of the unit of block.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.98.5-98
• /
• 2002

1. Introduction 2. System Overview 3. Tracking and Auto Zooming algorithm 3.2 Automatic ROI Setting 3.3 Escaping of the local distracters 4. Pan/Tilt Control System, Performance Evaluation 5. Conclusion