- 期刊
Multi-Modal Image Retrieval by Integrating Web Image Annotation, Concept Matching and Fuzzy Ranking Techniques
並列摘要
Traditional image retrieval aims at bridging visual images and human concepts through visual or textual descriptions. However, it is still a challenging issue to reduce the gap between the images and user's intentions. To this end, a considerable number of studies in the field of multimedia mining have been conducted on how to effectively meet the user's requirements for image retrieval over the past few decades. However, there remain some problems unsettled. For content-based image retrieval, it is not easy to identify the user's interest by using visual descriptions only. For textual-based image retrieval, the modern search engines incur the problems of high manual tagging cost and low automated tagging precision. Moreover, precise image retrieval also leads unsatisfied results because of the rough human concepts. To catch user's concept well, we propose a novel approach, namely Intelligent SeMantic Image explorER (iSMIER), which considers the requirements of usability, intelligence and effectiveness simultaneously. Based on the proposed web image annotation, concept matching and fuzzy ranking methods, the users can obtain the desired images from the image collection easily and effectively. Through empirical evaluations, our annotation models can deliver high accuracy for serving semantic image retrieval.
延伸閱讀
- Hung, M. W. (2007). Automatic Image Annotation Using a Semi-Supervised and Hierarchical Approach [master's thesis, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU.2007.00979
- 蔡哲平（2019）。Multi-label Classification Techniques with Generative Adversarial Network and Optimal Completion Distillation〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU201901512
- 張騉翔（2006）。A New Relevance Feedback Technique For Content-Based Image Retrieval〔碩士論文，國立暨南國際大學〕。華藝線上圖書館。https://doi.org/10.6837/NCNU.2006.00031
- Lin, H. C. (2005). A Study of Information Hiding and Image Retrieval Techniques for compressed Images [master's thesis, National Taichung University of Science and Technology]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0061-1811200915323506
- 周玟伶（2011）。Design of Content-Based Image Retrieval Techniques Using Relevant Features and Intelligent Learning Algorithms〔碩士論文，國立虎尾科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0028-2907201113303000