✦ LIBER ✦

Matching word images for content-based retrieval from printed document images

✍ Scribed by Million Meshesha; C. V. Jawahar

Publisher: Springer-Verlag
Year: 2008
Tongue: English
Weight: 461 KB
Volume: 11
Category: Article
ISSN: 1433-2833
DOI: 10.1007/s10032-008-0067-3

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Cluster-based color matching for image r

Cluster-based color matching for image retrieval

✍ Mohan S. Kankanhalli; Babu M. Mehtre; Ran Kang Wu 📂 Article 📅 1996 🏛 Elsevier Science 🌐 English ⚖ 613 KB

Natural language processing versus conte

Natural language processing versus content-based image analysis for medical document retrieval

✍ Aurélie Névéol; Thomas M. Deserno; Stéfan J. Darmoni; Mark Oliver Güld; Alan R. 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 408 KB 👁 3 views

Multiple representations, similarity mat

Multiple representations, similarity matching, and results fusion for content-based image retrieval

✍ Noureddine Abbadeni 📂 Article 📅 2005 🏛 Springer US 🌐 English ⚖ 565 KB

Edge based features for content based im

Edge based features for content based image retrieval

✍ Minakshi Banerjee; Malay K. Kundu 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 854 KB

The common problem in content based image retrieval (CBIR) is selection of features. Image characterization with lesser number of features involving lower computational cost is always desirable. Edge is a strong feature for characterizing an image. This paper presents a robust technique for extracti

Bayesian relevance feedback for content-

Bayesian relevance feedback for content-based image retrieval

✍ Giorgio Giacinto; Fabio Roli 📂 Article 📅 2004 🏛 Elsevier Science 🌐 English ⚖ 222 KB

Series feature aggregation for content-b

Series feature aggregation for content-based image retrieval

✍ Jun Zhang; Lei Ye 📂 Article 📅 2010 🏛 Elsevier Science 🌐 English ⚖ 718 KB

Feature aggregation is a critical technique in content-based image retrieval (CBIR) systems that employs multiple visual features to characterize image content. Most previous feature aggregation schemes apply parallel topology, e.g., the linear combination scheme, which suffer from two problems. Fir