Showing 3 results for Ocr
R. Ebrahimpour, S. Sarhangi, F. Sharifizadeh,
Volume 7, Issue 4 (12-2011)
Abstract
This paper presents the results of Persian handwritten word recognition based on Mixture of Experts technique. In the basic form of ME the problem space is automatically divided into several subspaces for the experts, and the outputs of experts are combined by a gating network. In our proposed model, we used Mixture of Experts Multi Layered Perceptrons with Momentum term, in the classification Phase. We produce three different Mixture of Experts structure. Experimental result for proposed method show an error rate reduction of 6.42 % compare to the mixture of MLPs experts. Comparison with some of the most related methods indicates that the proposed model yields excellent recognition rate in handwritten word recognition.
S. Mozaffari, A. A. Hajian Nezhad,
Volume 10, Issue 3 (9-2014)
Abstract
One of the related problems of OCR systems is discrimination of fonts in machine printed document images. This task improves performance of general OCR systems. Proposed methods in this paper are based on various fractal dimensions for font discrimination. First, some predefined fractal dimensions were combined with directional methods to enhance font differentiation. Then, a novel fractal dimension was introduced in this paper for the first time. Our feature extraction methods which consider font recognition as texture identification are independent of document content. Experimental results on different pages written by several font types show that fractal geometry can overcome the complexities of font recognition problem.
A. Vahedi, A. Baktash,
Volume 11, Issue 1 (3-2015)
Abstract
Recently, tape wound cores due to their excellent magnetic properties, are widely used in different types of transformers. Performance prediction of these transformers needs an accurate model with ability to determine flux distribution within the core and magnetic loss. Spiral structure of tape wound cores affects the flux distribution and always cause complication of analysis. In this paper, a model based on reluctance networks method is presented for analysis of magnetic flux in wound cores. Using this model, distribution of longitudinal and transverse fluxes within the core can be determined. To consider the nonlinearity of the core, a dynamic hysteresis model is included in the presented model. Having flux density in different points of the core, magnetic losses can be calculated. To evaluate the validity of the model, results are compared with 2-D FEM simulations. In addition, a transformer designed for series-resonant converter and simulation results are compared with experimental measurements. Comparisons show accuracy of the model besides simplicity and fast convergence
