영상 객체의 특징 추출을 이용한 내용 기반 영상 검색 시스템

• 영문명: Content-Based Image Retrieval System using Feature Extraction of Image Object
• 발행기관: 한국산업경영시스템학회
• 저자명: 정세환(Seh-Hwan Jung) 서광규(Kwang-Kyu Seo)
• 간행물 정보: 『산업경영시스템학회지』제27권 제3호, 59~65쪽, 전체 7쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2004.09.01

영문 초록

This paper explores an image segmentation and representation method using Vector Quantization(VQ) on color and texture for content-based image retrieval system. The basic idea is a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. These schemes are used for object-based image retrieval. Features for image retrieval are three color features from HSV color model and five texture features from Gray-level co-occurrence matrices. Once the feature extraction scheme is performed in the image, 8-dimensional feature vectors represent each pixel in the image. VQ algorithm is used to cluster each pixel data into groups. A representative feature table based on the dominant groups is obtained and used to retrieve similar images according to object within the image. The proposed method can retrieve similar images even in the case that the objects are translated, scaled, and rotated.

목차

1.서론

2.영상 특징 추출

3.대표 특징치 추출

4.객체의 특징치를 이용한 영상검색

5.실험 및 결과

6.결론

참고문헌