Handwritten Bangla Word Recognition using HOG Descriptor

被引：14
|
作者：
Bhowmik, Showmik [1 ]
Roushan, Md. Galib [1 ]
Sarkar, Ram [1 ]
Nasipuri, Mita [1 ]
Polley, Sanjib [2 ]
Malakar, Samir [3 ]
机构：
[1] Jadavpur Univ, Dept Comp Sc & Engg, Kolkata, India
[2] MCKV Inst Engn, Dept Comp Sc & Engg, Howrah, India
[3] MCKV Inst Engn, Dept Master Comp Applicat, Howrah, India
来源：
2014 FOURTH INTERNATIONAL CONFERENCE OF EMERGING APPLICATIONS OF INFORMATION TECHNOLOGY (EAIT) | 2014年
关键词：
Holistic word recognition; handwritten words; Histograms of oriented gradients; Bangla script;
D O I：
10.1109/EAIT.2014.43
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The holistic approaches for handwritten word recognition treat the words as single, indivisible entity and attempt to recognize words from their overall shape. In the present work, a novel technique to recognize handwritten Bangla word is proposed. Histograms of Oriented Gradients (HOG) are used as the feature set to represent each word sample at the feature space and a neural network based classifier is applied to classify the word images. On the basis of the HOG feature set, the performance achieved by the technique on a small dataset is quite satisfactory.
引用
收藏
页码：193 / 197
页数：5
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