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논문 기본정보
Framework for Content-Based Image Identification with Standardized Multiview Features
논문 개요
| 기관명 | NDSL |
|---|---|
| 저널명 | ETRI journal |
| ISSN | 1225-6463,2233-7326 |
| ISBN |
논문저자 및 소속기관 정보
| 저자(한글) | Das, Rik,Thepade, Sudeep,Ghosh, Saurav |
|---|---|
| 저자(영문) | |
| 소속기관 | |
| 소속기관(영문) | |
| 출판인 | |
| 간행물 번호 | |
| 발행연도 | 2016-01-01 |
| 초록 | Information identification with image data by means of low-level visual features has evolved as a challenging research domain. Conventional text-based mapping of image data has been gradually replaced by content-based techniques of image identification. Feature extraction from image content plays a crucial role in facilitating content-based detection processes. In this paper, the authors have proposed four different techniques for multiview feature extraction from images. The efficiency of extracted feature vectors for content-based image classification and retrieval is evaluated by means of fusion-based and data standardization-based techniques. It is observed that the latter surpasses the former. The proposed methods outclass state-of-the-art techniques for content-based image identification and show an average increase in precision of 17.71% and 22.78% for classification and retrieval, respectively. Three public datasets - Wang; Oliva and Torralba (OT-Scene); and Corel - are used for verification purposes. The research findings are statistically validated by conducting a paired t-test. |
| 원문URL | http://click.ndsl.kr/servlet/OpenAPIDetailView?keyValue=03553784&target=NART&cn=JAKO201650661372150 |
| 첨부파일 |
추가정보
| 과학기술표준분류 | |
|---|---|
| ICT 기술분류 | |
| DDC 분류 | |
| 주제어 (키워드) | Local threshold,partial coefficients,morphological operator,gray-level co-occurrence matrix,feature extraction,classification,retrieval,t-test |