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일반품질연구 : 양산단계 군수품에 대한 정부품질보증활동 실효성 향상 방안
신병철 ( Byung Cheol Shin ),황우열 ( Woo Yull Hwang ),안남수 ( Nam Su Ahn ),김덕환 ( Deok Hwan Kim ),이계림 ( Gye Lim Lee ),장봉기 ( Bong Ki Jang ),변재현 ( Jai Hyun Byun ) 한국품질경영학회 2016 품질경영학회지 Vol.44 No.1
Purpose: Government quality assurance (QA) activities in Korea, which is carried out by the Defense Agency for Technology and Quality, is not effective due to 1) the obscureness of the QA implementation method, 2) the gap between QA activities of provisions and those conducted in the fields, and 3) the variation in subjective judgement among the QA personnel. The purpose of this paper is to propose some suggestions to enhance the effectiveness of government QA activities for military supplies in the production stage. Methods: QA activities for military supplies are investigated and problematic aspects are deduced for the production stage. To secure the effectiveness of the QA activities, Defense Contract Management Agency of the United Sates is benchmarked and five improvement methods are presented. Results: Five improvement aspects are 1) reflecting special terms and conditions of government mandatory inspection in contract, 2) classifying QA personnel, 3) making use of data collection and analysis template compulsory, 4) providing checklist for process review, and 5) establishing guidelines for sampling plans for product examination. Conclusion: Suggestions of this paper can lead to consistency and balance in government QA activities, reducing military suppliers` complaints and enhancing the effectiveness of QA effort, and ultimately contributing to the quality improvement of military supplies.
크기 및 회전 불변 영역 특징을 이용한 이미지 유사성 검색
유승훈(Seung-Hoon Yu),김현수(Hyun-Soo Kim),이석룡(Seok-Lyong Lee),임명관(Myung-Kwan Lim),김덕환(Deok-Hwan Kim) 한국정보과학회 2009 정보과학회논문지 : 데이타베이스 Vol.36 No.6
다양한 영역 검출 및 형태 특징 추출 방법 중에서 MSER과 SIFT를 응용한 방법들이 컴퓨터비전 분야에 많이 사용된다. 하지만 기존의 SIFT를 이용한 특징 추출 방법은 밝기 변화에 민감한 특성을 지니며, MSER 방법은 이미지의 크기 변화에 민감하고, 이미지 유사성 검색에 그대로 적용하기에는 어려움이 많다. 본 논문에서는 스케일 피라미드, MSER 그리고 어파인(affine) 정규화 과정 등을 이용한 영역 특징 서술자를 제안한다. 제안한 방법은 어파인 정규화 방법과 스케일 피라미드를 사용하기 때문에 이미지의 크기, 회전 및 밝기 변화에 불변하다. 다양한 이미지들을 이용하여 실험하고, 실험 결과에서 제안한 방법이 SIFT, PCA-SIFT, CE-SIFT 그리고 SURF 방법에 비해서 각각 20%, 38%, 11%, 24% 이상 좋은 이미지 검색 성능을 보이고 있다. Among various region detector and shape feature extraction method, MSER(Maximally Stable Extremal Region) and SIFT and its variant methods are popularly used in computer vision application. However, since SIFT is sensitive to the illumination change and MSER is sensitive to the scale change, it is not easy to apply the image similarity retrieval. In this paper, we present a Scale and Rotation Invariant Region Feature(SRIRF) descriptor using scale pyramid, MSER and affine normalization. The proposed SRIRF method is robust to scale, rotation, illumination change of image since it uses the affine normalization and the scale pyramid. We have tested the SRIRF method on various images. Experimental results demonstrate that the retrieval performance of the SRIRF method is about 20%, 38%, 11%, 24% better than those of traditional SIFT, PCA-SIFT, CE-SIFT and SURF, respectively.