• Journal of the Korean Society for Precision Engineering
• /
• v.25 no.2
• /
• pp.131-139
• /
• 2008

This paper presents a new saliency map which is constructed by providing dynamic weights on individual features in an input image to search ROI(Region Of Interest) or FOA(Focus Of Attention). To construct a saliency map on there is no a priori information, three feature-maps are constructed first which emphasize orientation, color, and intensity of individual pixels, respectively. From feature-maps, conspicuity maps are generated by using the It's algorithm and their information quantities are measured in terms of entropy. Final saliency map is constructed by summing the conspicuity maps weighted with their individual entropies. The prominency of the proposed algorithm has been proved by showing that the ROIs detected by the proposed algorithm in ten different images are similar with those selected by one-hundred person's naked eyes.

• International Journal of Contents
• /
• v.11 no.4
• /
• pp.77-85
• /
• 2015

Table detection is a challenging problem and plays an important role in document layout analysis. In this paper, we propose an effective method to identify the table region from document images. First, the regions of interest (ROIs) are recognized as the table candidates. In each ROI, we locate text components and extract text blocks. After that, we check all text blocks to determine if they are arranged horizontally or vertically and compare the height of each text block with the average height. If the text blocks satisfy a series of rules, the ROI is regarded as a table. Experiments on the ICDAR 2013 dataset show that the results obtained are very encouraging. This proves the effectiveness and superiority of our proposed method.

• Journal of Multimedia Information System
• /
• v.5 no.1
• /
• pp.35-42
• /
• 2018

Direct volume rendering (DVR) is an important 3D visualization method for medical images as it depicts the full volumetric data. However, because DVR renders the whole volume, regions of interests (ROIs) such as a tumor that are embedded within the volume maybe occluded from view. Thus, conventional 2D cross-sectional views are still widely used, while the advantages of the DVR are often neglected. In this study, we propose a new visualization algorithm where we augment the 2D slice of interest (SOI) from an image volume with volumetric information derived from the DVR of the same volume. Our occlusion-based DVR augmentation for SOI (ODAS) uses the occlusion information derived from the voxels in front of the SOI to calculate a depth parameter that controls the amount of DVR visibility which is used to provide 3D spatial cues while not impairing the visibility of the SOI. We outline the capabilities of our ODAS and through a variety of computer tomography (CT) medical image examples, compare it to a conventional fusion of the SOI and the clipped DVR.

• Proceedings of the Korean Society of Toxicology Conference
• /
• 2003.05a
• /
• pp.91-92
• /
• 2003

Oxidative stress induced by reactive oxygen intermediates (ROIs) has been implicated in a variety of human diseases including cancer, diabetes, rheumatoid arthritis and neurodegenerative disorders. Hydrogen peroxide ($H_2O$$_2$), a representative ROI which is produced during the cellular redox process, can cause cell death via apoptosis and/or necrosis depending on its concentrations. (omitted)

• International Journal of Contents
• /
• v.8 no.4
• /
• pp.56-63
• /
• 2012

In recent decades, analyzing the activities of human brain achieved some accomplishments by using the functional Magnetic Resonance Imaging (fMRI) technique. fMRI data provide a sequence of three-dimensional images related to human brain's activity which can be used to detect instantaneous cognitive states by applying machine learning methods. In this paper, we propose a new approach for distinguishing human's cognitive states such as "observing a picture" versus "reading a sentence" and "reading an affirmative sentence" versus "reading a negative sentence". Since fMRI data are high dimensional (about 100,000 features in each sample), extremely sparse and noisy, feature selection is a very important step for increasing classification accuracy and reducing processing time. We used the Fisher Discriminant Ratio to select the most powerful discriminative features from some Regions of Interest (ROIs). The experimental results showed that our approach achieved the best performance compared to other feature extraction methods with the average accuracy approximately 95.83% for the first study and 99.5% for the second study.

• Journal of the Korean Society for Library and Information Science
• /
• v.13
• /
• pp.121-142
• /
• 1986

Au debut de la dynastie de Choson, qui represente une periode de la regne des rois T'aejo et T'aejong, il fallait etablir et codifier la .nouvelle politique nationale, et c'est dans ce contexte que les caracteres kyemi, qui ont joue Ie role tres important dans l'histoire de la typographie mondiale, furent crees. Le sujet de ce memoire n'est qu'une enumeration des faits historiques de l'edition ou de l'imprimerie dans cet epoque, mais une recherche sur la vraie signification de la culture du livre imprime. Done, on peut etudier ici; d'abord, less activites de l'imprimerie a l'epoque du roi T'aejo et du roi T'aejong, et enfin, la signification et le bilan synthetique de ces activites, surtout des caracteres kyemi sur le point de l'histoire de la civilisation mondiale.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.7
• /
• pp.1100-1104
• /
• 2017

A detector-based approach shows the limited performances for the defect inspections such as shallow fine cracks and indistinguishable defects from background. Deep learning technique is widely used for object recognition and it's applications to detect defects have been gradually attempted. Deep learning requires huge scale of learning data, but acquisition of data can be limited in some industrial application. The possibility of applying CNN which is one of the deep learning approaches for surface defect inspection is investigated for industrial parts whose detection difficulty is challenging and learning data is not sufficient. VOV is adopted for pre-processing and to obtain a resonable number of ROIs for a data augmentation. Then CNN method is applied for the classification. Three CNN networks, AlexNet, VGGNet, and mofified VGGNet are compared for experiments of defects detection.

• Proceedings of the PSK Conference
• /
• 2003.10b
• /
• pp.153.1-153.1
• /
• 2003

Oxidative stress induced by reactive oxygen intermediates (ROIs) has been implicated in a variety of human diseases including cancer, diabetes, rheumatoid arthritis and neurodegenerative disorders. Hydrogen peroxide ($H_2O_2$), a representative ROI which is produced during the cellular redox process, can cause cell death via apoptosis and/or necrosis depending on its concentrations. l5-Deoxy-$D^{12, 14}$ prostaglandin $J_2$ (15d-$PGJ_2$), a dehydration product of prostaglandin $D_2$, has been reportd to possess a number of biological activities such as anti-inflammatory, anticarcinogenic, and antioxidative properties. (omitted)

• Proceedings of the Korea Information Processing Society Conference
• /
• 2011.11a
• /
• pp.314-317
• /
• 2011

본 논문은 상향식 현저함 모델을 이용하여 입력 영상으로부터 시각적 주의를 갖는 영역들을 자동으로 검출하는 방법을 제안한다. 제안한 방법에서는 인간의 시각 시스템과 같이 사전 지식 없이 시각정보의 공간적인 분포에 근거하여 장면을 해석하는 상향식 현저함 모델 방법을 입력 영상에 적용하여 관심 물체 영역을 검출하는 연구이다. 상향식 현저함 방법은 Treisman의 세부특징이론 연구에서 제시한 바와 같이 시각적 주의를 갖는 영역은 시각정보의 현격한 대비차이를 가지는 영역으로 집중되어 배경에서 관심영역을 구분할 수 있다. 입력 영상에서 현저함 모델을 통해 3차원 현저함 맵을 생성한다. 그리고 생성된 현저함 맵으로부터 실제 관심영역들을 검출하기 위해 제안한 방법에서는 적응적 임계치 방법을 적용하여 관심영역을 검출한다. 제안한 방법을 관심영역 분할에 적용한 결과, 영역 분할 정확도 및 정밀도가 약 88%와 89%로 제시되어 관심 영상분할 시스템에 적용이 가능함을 알 수 있다.

• Progress in Medical Physics
• /
• v.9 no.3
• /
• pp.155-162
• /
• 1998

Ho-l66 was produced by neutron reaction in a reactor at the Korea Atomic Energy Institute (Taejon, Korea). Ho-l66 emits a high energy beta particles with a maximum energy of 1.85 MeV and small proportion of gamma rays (80 keV). Therefore, the radiation absorbed dose estimation could be based on the in-vivo quantification of the activity in tumors from the gamma camera images. Approximately 1 mCi of Ho-l66 in solution was mixed into the flood phantom and planar scintigraphic images were acquired with and without patient interposed between the phantom and scintillation camera. Transmission factor over an area of interest was calculated from the ratio of counts in selected regions of the two images described above. A dual-head gamma camera(Multispect2, Siemens, Hoffman Estates, IL, USA) equipped with medium energy collimators was utilized for imaging(80 keV${\pm}$10%). Fifty-nine year old female patient with hepatoma was enrolled into the therapeutic protocol after the informed consent obtained. Thirty millicuries(110MBq) of Ho-166-CHICO was injected into the right hepatic arterial branch supplying hepatoma. When the injection was completed, anterior and posterior scintigraphic views of the chest and pelvic regions were obtained for 3 successive days. Regions of interest (ROIs) were drawn over the organs in both the anterior and posterior views. The activity in those ROIs was estimated from geometric mean, calibration factor and transmission factors. Absorbed dose was calculated using the Marinelli formula and Medical Internal Radiation Dose (MIRD) schema. Tumor dose of the patient treated with 1110 MBq(30 mCi) Ho-l66 was calculated to be 179.7 Gy. Dose distribution to normal liver, spleen, lung and bone was 9.1, 10.3, 3.9, 5.0 % of the tumor dose respectively. In conclusion, tumor dose and absorbed dose to surrounding structures were calculated by daily external imaging after the Ho-l66 therapy for hepatoma. In order to limit the thresholding dose to each surrounding organ, absorbed dose calculation provides useful information.