Multi-modal Information Integration for Document Retrieval

被引:3
|
作者
Hassan, Ehtesham [1 ]
Chaudhury, Santanu [1 ]
Gopal, M. [2 ]
机构
[1] Indian Inst Technol Delhi, Dept Elect Engn, Delhi, India
[2] SNU, Sch Engn, Gautam Buddha Nagar, India
关键词
Document Indexing; Multi-modal Retrieval; Multiple Kernel Learning; TEXT; SPACE;
D O I
10.1109/ICDAR.2013.243
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The paper proposes a novel multi-modal document image retrieval framework by exploiting the information of text and graphics regions. The framework applies multiple kernel learning based hashing formulation for generation of composite document indexes using different modalities. The existing multimedia management methods for imaged text documents have not addressed the requirement of old and degraded documents. In the subsequent contribution, we propose novel multi-modal document indexing framework for retrieval of old and degraded text documents by combining OCRed text and image based representation using learning. The evaluation of proposed concepts is demonstrated on sampled magazine cover pages, and documents of Devanagari script.
引用
收藏
页码:1200 / 1204
页数:5
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