SVM-based hierarchical architectures for handwritten Bangla character recognition Export

@article{BhowmikGRP09, abstract = {Abstract\ \ We propose support vector machine (SVM) based hierarchical classification schemes for recognition of handwritten Bangla characters. A comparative study is made among multilayer perceptron, radial basis function network and SVM classifier for this 45 class recognition problem. SVM classifier is found to outperform the other classifiers. A fusion scheme using the three classifiers is proposed which is marginally better than SVM classifier. It is observed that there are groups of characters having similar shapes. These groups are determined in two different ways on the basis of the confusion matrix obtained from SVM classifier. In the former, the groups are disjoint while they are overlapped in the latter. Another grouping scheme is proposed based on the confusion matrix obtained from neural gas algorithm. Groups are disjoint here. Three different two-stage hierarchical learning architectures (HLAs) are proposed using the three grouping schemes. An unknown character image is classified into a group in the first stage. The second stage recognizes the class within this group. Performances of the HLA schemes are found to be better than single stage classification schemes. The HLA scheme with overlapped groups outperforms the other two HLA schemes.}, author = {Bhowmik, Tapan and Ghanty, Pradip and Roy, Anandarup and Parui, Swapan}, citeulike-article-id = {4264134}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/s10032-009-0084-x}, citeulike-linkout-1 = {http://www.springerlink.com/content/m4v63275462n768u}, day = {1}, doi = {10.1007/s10032-009-0084-x}, journal = {International Journal on Document Analysis and Recognition}, keywords = {architectures, bangla, character, classes, fusion, grouping, handwritten, hierarchical, learning, mlp, of, rbf, recognition, svm}, month = {July}, number = {2}, pages = {97--108}, posted-at = {2009-07-23 12:30:55}, priority = {2}, title = {SVM-based hierarchical architectures for handwritten Bangla character recognition}, url = {http://dx.doi.org/10.1007/s10032-009-0084-x}, volume = {12}, year = {2009} }

TY - JOUR ID - BhowmikGRP09 L3 - citeulike-article-id:4264134 N2 - Abstract  We propose support vector machine (SVM) based hierarchical classification schemes for recognition of handwritten Bangla characters. A comparative study is made among multilayer perceptron, radial basis function network and SVM classifier for this 45 class recognition problem. SVM classifier is found to outperform the other classifiers. A fusion scheme using the three classifiers is proposed which is marginally better than SVM classifier. It is observed that there are groups of characters having similar shapes. These groups are determined in two different ways on the basis of the confusion matrix obtained from SVM classifier. In the former, the groups are disjoint while they are overlapped in the latter. Another grouping scheme is proposed based on the confusion matrix obtained from neural gas algorithm. Groups are disjoint here. Three different two-stage hierarchical learning architectures (HLAs) are proposed using the three grouping schemes. An unknown character image is classified into a group in the first stage. The second stage recognizes the class within this group. Performances of the HLA schemes are found to be better than single stage classification schemes. The HLA scheme with overlapped groups outperforms the other two HLA schemes. IS - 2 JF - International Journal on Document Analysis and Recognition EP - 108 TI - SVM-based hierarchical architectures for handwritten Bangla character recognition VL - 12 SP - 97 KW - architectures KW - bangla KW - character KW - classes KW - fusion KW - grouping KW - handwritten KW - hierarchical KW - learning KW - mlp KW - of KW - rbf KW - recognition KW - svm AU - Bhowmik, Tapan AU - Ghanty, Pradip AU - Roy, Anandarup AU - Parui, Swapan PY - 2009/07/01/ UR - http://dx.doi.org/10.1007/s10032-009-0084-x ER -