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| Chew Lim Tan, Weihua Huang, Zhaohui Yu, Yi Xu, "Imaged Document Text Retrieval Without OCR," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 6, pp. 838-844, June, 2002. | |||
| BibTex | x | ||
| @article{ 10.1109/TPAMI.2002.1008389, author = {Chew Lim Tan and Weihua Huang and Zhaohui Yu and Yi Xu}, title = {Imaged Document Text Retrieval Without OCR}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {24}, number = {6}, issn = {0162-8828}, year = {2002}, pages = {838-844}, doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2002.1008389}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - Imaged Document Text Retrieval Without OCR IS - 6 SN - 0162-8828 SP838 EP844 EPD - 838-844 A1 - Chew Lim Tan, A1 - Weihua Huang, A1 - Zhaohui Yu, A1 - Yi Xu, PY - 2002 KW - Document image analysis KW - document vector KW - text similarity KW - textretrieval. VL - 24 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
We propose a method for text retrieval from document images without the use of OCR. Documents are segmented into character objects. Image features, namely, the Vertical Traverse Density (VTD) and Horizontal Traverse Density (HTD), are extracted. An n-gram based document vector is constructed for each document based on these features. Text similarity between documents is then measured by calculating the dot product of the document vectors. Testing with seven corpora of imaged textual documents in English and Chinese as well as images from UW1 database confirms the validity of the proposed method.
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