Proceedings ArticleDOI
Use of MKL as symbol classifier for Gujarati character recognition
Ehtesham Hassan,Santanu Chaudhury,M. Gopal,Jignesh Dholakia +3 more
- pp 255-262
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TLDR
The MKL based classification is proposed, where the MKL is used for learning optimal combination of different features for classification and the comparison results in 1-Vs-1 framework and using KNN classifier are presented.Abstract:
The present work is part of ongoing effort to improve the performance of Gujarati character recognition. In the recent advancement in kernel methods, the novel concept of multiple kernel learning(MKL) has given improved results for many problems. In this paper, we present novel application of MKL for Gujarati character recognition. We have applied three different feature representations for symbols obtained after zone wise segmentation of Gujarati text. The MKL based classification is proposed, where the MKL is used for learning optimal combination of different features for classification. In addition MKL based classification results for different features is also presented. The multiclass classification is performed in Decision DAG framework. The comparison results in 1-Vs-1 framework and using KNN classifier is also presented. The experiments have shown substantial improvement in earlier results.read more
Citations
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Journal ArticleDOI
Word shape descriptor-based document image indexing: a new DBH-based approach
TL;DR: The exhaustive experimental evaluation of the proposed framework on a collection of documents belonging to Devanagari, Bengali and English scripts has yielded encouraging results.
Journal ArticleDOI
Feature combination for binary pattern classification
TL;DR: A novel binary multiple kernel learning-based classification architecture for applications including characters/primitives and symbols including such problems for fast and efficient performance is demonstrated.
Book ChapterDOI
Structural Feature Based Classification of Printed Gujarati Characters
Mukesh M. Goswami,Suman K. Mitra +1 more
TL;DR: This paper presents a Structural feature based method for classification of printed Gujarati characters that deals with varied sizes, font styles, and stoke widths.
Recognition of Gujarati Numerals using Hybrid Approach and Neural Networks
M J Baheti,K V Kale +1 more
TL;DR: A hybrid approach for recognition of Gujarati handwritten numerals using neural networks as classifier and achieved a good recognition rate for noisy numerals is presented.
Proceedings ArticleDOI
Document Image Indexing Using Edit Distance Based Hashing
TL;DR: A novel word image based document indexing scheme by combination of string matching and hashing is presented for two document image collections belonging to Devanagari and Bengali script.
References
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Proceedings ArticleDOI
Histograms of oriented gradients for human detection
Navneet Dalal,Bill Triggs +1 more
TL;DR: It is shown experimentally that grids of histograms of oriented gradient (HOG) descriptors significantly outperform existing feature sets for human detection, and the influence of each stage of the computation on performance is studied.
Journal ArticleDOI
Learning the Kernel Matrix with Semidefinite Programming
Gert R. G. Lanckriet,Nello Cristianini,Peter L. Bartlett,Laurent El Ghaoui,Michael I. Jordan +4 more
TL;DR: This paper shows how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques and leads directly to a convex method for learning the 2-norm soft margin parameter in support vector machines, solving an important open problem.
Proceedings Article
Large Margin DAGs for Multiclass Classification
TL;DR: An algorithm, DAGSVM, is presented, which operates in a kernel-induced feature space and uses two-class maximal margin hyperplanes at each decision-node of the DDAG, which is substantially faster to train and evaluate than either the standard algorithm or Max Wins, while maintaining comparable accuracy to both of these algorithms.
Journal ArticleDOI
Sequential Operations in Digital Picture Processing
Azriel Rosenfeld,John L. Pfaltz +1 more
TL;DR: The relative merits of performing local operations on ~ digitized picture in parallel or sequentially are discussed and some applications of the connected component and distance functions are presented.
Journal Article
Large Scale Multiple Kernel Learning
TL;DR: It is shown that the proposed multiple kernel learning algorithm can be rewritten as a semi-infinite linear program that can be efficiently solved by recycling the standard SVM implementations, and generalize the formulation and the method to a larger class of problems, including regression and one-class classification.