• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.959-962
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• 1988

This paper describes an automatic visual inspection system for fabric defects based on pattern recognition techniques. The inspection for fabric defects can be separated into three sequences of operations which are the detection of fabric defects[1], the classification of figures of fabric defects, and the classification of fabric defects. Comparing projections of defect-detected images with the predefined complex, the classification accuracy of figures of fabric defects was found to be 95.3 percent. Employing the Bayes classifier using cluster shade in SGLDM and variance in decorrelation method as features, the classification accuracy of regional figure defects was found to be 82.4 percent. Finally, some experimental results for line and dispersed figures of fabric defects are included.

• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.17.2-17
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• 2001

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.12
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• pp.67-72
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• 1993

An adaptive block truncation coding(BTC) using human visual system(HVS) is proposed. To reduce visible blocking effect at sensitive area in HVS. a new category classification coefficient is proposed. The categroy classification coefficient was derived by combining the modified HVS and standard deviation. By computer simulations, we showed that the proposed method reduced blocking effect at low bit rate coding more than the conventional Hui's method.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2108-2111
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• 2003

This paper introduces a new local feature extraction method and image matching method for the localization and classification of targets. Proposed method is based on the block-by-block projection associated with directional pattern of blocks. Each pattern has its own eigen-vertors called as CEBs(Classified Eigen-Blocks). Also proposed block-based image matching method is robust to translation and occlusion. Performance of proposed feature extraction and matching method is verified by the face localization and FLIR-vehicle-image classification test.

• Journal of Korean Society of Archives and Records Management
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• v.11 no.2
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• pp.217-247
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• 2011

Archival arrangement is essential process to preserve the context of art archives creation and accumulation while classification is important to search archival collections by their topic, type or business process. But archival arrangement is not being taken seriously in most art archives in Korea. The purpose of this study is to analyse the arrangement and classification issues of art archives in Korea, and to suggest some principles and strategies for organizing art archives more systematically. This paper begins with identifying the difference between arrangement and classification and analyses some cases of visual and performing art archives in Korea and United States in terms of archival organization. Based on these analyses, it gives some suggestions for improving the quality of arrangement and classification in Korean art archives.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.299-308
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• 2014

Various literatures related computing of information processing have been recently shown the researches inspired from the remarkably excellent human capabilities which recognize and categorize very complex visual patterns such as body motions and facial expressions. Applied from human's outstanding ability of perception, the classification function of visual sequences without context information is specially crucial task for computer vision to understand both the coding and the retrieval of spatio-temporal patterns. This paper presents a biological process based action recognition model of computer vision, which is inspired from visual information processing of human brain for action recognition of visual sequences. Proposed model employs the structure of neural fields of bio-inspired visual perception on detecting motion sequences and discriminating visual patterns in human brain. Experimental results show that proposed recognition model takes not only into account several biological properties of visual information processing, but also is tolerant of time-warping. Furthermore, the model allows robust temporal evolution of classification compared to researches of action recognition. Presented model contributes to implement bio-inspired visual processing system such as intelligent robot agent, etc.

• Korean Journal of Radiology
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• v.21 no.8
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• pp.998-1006
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• 2020

Objective: To compare the accuracies of quantitative computed tomography (CT) parameters and semiquantitative visual score in evaluating clinical classification of severity of coronavirus disease (COVID-19). Materials and Methods: We retrospectively enrolled 187 patients with COVID-19 treated at Tongji Hospital of Tongji Medical College from February 15, 2020, to February 29, 2020. Demographic data, imaging characteristics, and clinical data were collected, and based on the clinical classification of severity, patients were divided into groups 1 (mild) and 2 (severe/critical). A semiquantitative visual score was used to estimate the lesion extent. A three-dimensional slicer was used to precisely quantify the volume and CT value of the lung and lesions. Correlation coefficients of the quantitative CT parameters, semiquantitative visual score, and clinical classification were calculated using Spearman's correlation. A receiver operating characteristic curve was used to compare the accuracies of quantitative and semi-quantitative methods. Results: There were 59 patients in group 1 and 128 patients in group 2. The mean age and sex distribution of the two groups were not significantly different. The lesions were primarily located in the subpleural area. Compared to group 1, group 2 had larger values for all volume-dependent parameters (p < 0.001). The percentage of lesions had the strongest correlation with disease severity with a correlation coefficient of 0.495. In comparison, the correlation coefficient of semiquantitative score was 0.349. To classify the severity of COVID-19, area under the curve of the percentage of lesions was the highest (0.807; 95% confidence interval, 0.744-0.861: p < 0.001) and that of the quantitative CT parameters was significantly higher than that of the semiquantitative visual score (p = 0.001). Conclusion: The classification accuracy of quantitative CT parameters was significantly superior to that of semiquantitative visual score in terms of evaluating the severity of COVID-19.

• Journal of the Korean Society of Costume
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• v.52 no.6
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• pp.51-69
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• 2002

The purpose of this study was to classify the body shapes. exclusive of size and corpulence factors of more than 60-year old elderly women by distinctions, and to investigate the visual effects of combination of ensemble suit details. For the body shape classification, the factor analysis and cluster analysis were performed : the mean value difference of numeral values for classified types were tested by ANOVA : and the follow-up test was conducted by the Duncan's multiple ranged test. The data analysis for visual effects evaluated by a multiple ranking test was analysed by mean. paired t-test, ANOVA and Duncan's multiple ranged test. The results are summarized as follows : 1. The followings are the types of body shape according to the shape factors of the front line of body for elderly women. The distinctions of the front li e of elderly women's body could be presumed; that was, Body typeⅠ was a comparatively well-balanced body type, Body type Ⅱ was close to an average body type. and Body type In was a severely corpulent body type. 2. The followings are the results on the physical visual effects inducing the constituents of clothing type. 1) The neckline·collar types of a jacket have a great influence on the visual effects of the upper body, and orderly. the tailored collar. soutien collar, and round neckline had positive influence on the visual effects in the upper body. 2) The pleat types of one-piece dress had positive influence on the visual effects in the lower body in the order of gored type, pleats type, and gathered type. Also. the balance in the lower body had more influence on the overall balance of the clothing compared to the constituents of clothing type such as neckline collar type or opening line. 3) It showed that whether there is the front opening line of a jacket influenced on the visual effects of all categories.

• Archives of Plastic Surgery
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• v.34 no.6
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• pp.719-723
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• 2007

Purpose: Blowout fracture can lead to functional impairments and esthetic deformities such as impairment of ocular movement, diplopia, visual loss and enophthalmos. The object of this study is to present a classification and its analysis according to the computed tomographic scan in blowout fractures. We classified blow out fractures into three types according to the anatomical location of fracture, the size of the bone defect and the degree of periosteal injury by using the computed tomography scan. Each progress and complications were analyzed more than mean 1 year. Methods: Among the 155 cases during 4 years, there were 11 cases of medial orbital wall fracture, 97 cases of inferior orbital wall fracture, 47 cases of combined type. The mean age of patients was 31.2 years, ranged from 8 to 84 years. Results: According to our classification, surgical treatments through the nasoendoscopic approach, the subciliary approach, the transconjunctival approach or their combinations were performed in 116 patients, and conservative treatments were done in 46 patients. Presurgical clinical findings of diplopia, impairment of ocular movement, enophthalmos of more than 2 mm were present in 62 patients. After surgical treatment, clinical findings were remained in 7 patients. Conclusion: We think that our classification according to computed tomographic scan is helpful for the indication and it may decrease the complications such as impairment of ocular movement, diplopia, visual loss and enophthalmos.

• Journal of Korean Academy of Nursing
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• v.43 no.4
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• pp.526-535
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• 2013

Purpose: This study was done to compare clinical nurses' knowledge and visual differentiation diagnostic ability for the pressure ulcer classification system (PUCS) and incontinence-associated dermatitis (IAD). Methods: A convenience sample of 602 nurses took the pressure ulcer classification system and incontinence-associated dermatitis knowledge test (PUCS & IAD KT) and completed the visual differentiation tool (VDT), consisting of 21 photographs with clinical information. Results: The overall mean score for correct answers was 14.5 (${\pm}3.2$) in PUCS & IAD KT and 11.15 (${\pm}4.9$) in PUCS & IAD VDT. Incorrect responses were most common for statements related to stage III, IAD for PUCS & IAD KT, and suspected deep tissue injury (SDTI), unstageable, and stage III for PUCS & IAD VDT. Significant correlations were found between PUCS & IAD KT and VDT (r=.48, p<.001). Factors affecting scores for PUCS & IAD VDT were PUCS & IAD KT, frequency of pressure ulcer, IAD management and participation in wound care education programs. Conclusion: Results indicate that nurses have an overall understanding of PUCS & IAD, but low visual differentiation ability regarding stage III, SDTI, and unstageable ulcers. Continuing education is needed to further improve knowledge and visual differentiation ability for PUCS & IAD.