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2015 3rd IAPR Asian Conference on Pattern Recognition
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$EVWUDFW In this paper we present a line based word spotting system based on Hidden Markov Model for offline Indic scripts such as Bangla (Bengali) and Devanagari. We propose a novel approach of combining foreground and background information of text line images for keywordspotting by character filler models. The candidate keywords are searched from a line without segmenting character or words. A significant improvement in performance is noted by using both foreground and background information than anyone alone. Pyramid Histogram of Oriented Gradient (PHOG) feature has been used in our word spotting framework and it outperforms other existing features of word spotting. The framework of combining foreground and background information has been evaluated in IAM dataset (English script) to show the robustness of the proposed approach. ,QWURGXFWLRQ +DQGZULWWHQ WH[W UHFRJQLWLRQ LV VWLOO RQH RI WKH FKDOOHQJLQJ SUREOHPV LQ WKH ILHOG RI SDWWHUQ UHFRJQLWLRQ 'XH WR WKH IUHHIORZ QDWXUH RI KDQGZULWLQJ DQG PDQ\ ZULWLQJ YDULDWLRQV WKH UHFRJQLWLRQ SHUIRUPDQFH LV QRW VDWLVIDFWRU\ HYHQ ZLWK VRSKLVWLFDWHG SUHSURFHVVLQJ DQG 2&5 WHFKQLTXHV $ VSHFLDO IRUP RI ZRUG UHFRJQLWLRQ WHFKQLTXH WKH VR FDOOHG ³:RUG 6SRWWLQJ´ KDV EHHQ SURSRVHG >@ WKDW GRHV QRW UHTXLUH 2&5 RI WKH HQWLUH GRFXPHQW:RUGVSRWWLQJKDVEHHQH[WHQVLYHO\VWXGLHG> @WRGHWHFWDZRUGLQDKDQGZULWWHQGRFXPHQWSDJH RUOLQH DVSHUWKHXVHU¶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©2015 IEEE
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VFULSWV DUH VKRZQ LQ 7DEOH 6RPH TXDOLWDWLYH UHVXOWV LQ WKUHH VFULSWV DUH VKRZQ LQ )LJ 1RWH WKDW WKH V\VWHP LV HIILFLHQW ZLWK WKH KDQGZULWLQJ YDULDELOLW\ DQG VSDFH EHWZHHQFKDUDFWHUVLQDZRUG 7DEOH7KHGDWDVHWXVHGIRUWKHH[SHULPHQW Bangla
Devanagari
IAM(English)
Training
6824
6214
6029
Validation
854
810
822
Testing Keywords
914 671
878 621
875 821
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Table 2.Some examples of keywords Bangla Devanagari IAM (English) being Ċđñđþđĉ ͨȡ ĺĄĒĉíĠđĊđ
ǐȪȡ
House
ćþăđÿŪïƟ
ȯȯ
Government
ćĎđĂñĉē
ͧȡ
People
ċċēïĉ
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would
čáąđĀĀđþđ
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Should
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