Anandarup Roy

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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(More)
Character segmentation is a necessary preprocessing step for character recognition in many handwritten word recognition systems. The most difficult case in character segmentation is the cursive script. Fully cursive nature of Bangla handwriting, the natural skewness in words poses some challenges for automatic character segmentation. In this article a novel(More)
The goal of this article is twofold. First, it deals with color image segmentation in hue-saturation space. A model for circular data is provided by the vM-Gauss distribution, which is a joint distribution of von-Mises and Gaussian distributions. The mixture of vM-Gauss distributions is used to model hue-saturation data. After segmentation, a post(More)
Finite mixture models are widely used to perform model-based clustering of multivariate data sets. Most of the existing mixture models work with linear data; whereas, real-life applications may involve multivariate data having both circular and linear characteristics. No existing mixture models can accommodate such correlated circular–linear data. In this(More)
This article deals with mixture model based color image segmentation in the LCH color space. In this space, one of the components (representing hue in particular) is circular in nature. Hence LCH image pixels are samples on a cylinder. A statistical model for such data needs to employ circular-linear joint distributions. Here such a model is designed using(More)
This paper presents a finite mixture model that involves a pair-copula based construction of a multivariate distribution. The advantage of such a model is that the margins and the dependence structures are de-coupled from each other. Also, they could be modeled separately. In effect the mixture model (called DVMM) is capable of capturing a broader family of(More)
This article proposes a scheme for automatic extraction and recognition of Bangla text from natural scene images. An image, when captured by a digital camera may have perspective distortion. Before extracting text symbols, this distortion is corrected using Homography transform. For text extraction, headlines are detected using morphology. First, the(More)