An intelligent offline handwriting recognition system using evolutionary neural learning algorithm and rule based over segmented data points
- Authors: Ghosh, Ranadhir , Ghosh, Moumita
- Date: 2005
- Type: Text , Journal article
- Relation: Journal of Research and Practice in Information Technology Vol. 37, no. 1 (2005), p. 73-86
- Full Text: false
- Reviewed:
- Description: In this paper we propose a novel technique of using a hybrid evolutionary method, which uses a combination of genetic algorithm and matrix based solution methods such as QR factorization. The training of the model is based on a layer based hierarchical structure for the architecture and the weights for the Artificial Neural Network classifier. The architecture for the classifier is found using a binary search type procedure. The hierarchical structured algorithm (EALS-BT) is also a hybrid, because it combines the Genetic Algorithm based method with the Matrix based solution method for finding weights. A heuristic segmentation algorithm is initially used to over segment each word. Then the segmentation points are passed through the rule-based module to discard the incorrect segmentation points and include any missing segmentation points. Following the segmentation the contour is extracted between two correct segmentation points. The contour is passed through the feature extraction module that extracts the angular features, after which the EALS-BT algorithm finds the architecture and the weights for the classifier network. These recognized characters are grouped into words and passed to a variable length lexicon that retrieves words that have the highest confidence value.
- Description: C1
- Description: 2003001367
A novel approach for structural feature extraction : Contour vs. direction
- Authors: Verma, Brijesh , Blumenstein, Michael , Ghosh, Moumita
- Date: 2004
- Type: Text , Journal article
- Relation: Pattern Recognition Letters Vol. 25, no. 9 (2004), p. 975-988
- Full Text: false
- Reviewed:
- Description: The paper presents a novel approach for extracting structural features from segmented cursive handwriting. The proposed approach is based on the contour code and stroke direction. The contour code feature utilises the rate of change of slope along the contour profile in addition to other properties such as the ascender and descender count, start point and end point. The direction feature identifies individual line segments or strokes from the character's outer boundary or thinned representation and highlights each character's pertinent direction information. Each feature is investigated employing a benchmark database and the experimental results using the proposed contour code based structural feature are very promising. A comparative evaluation with the directional feature and existing transition feature is included. © 2004 Elsevier B.V. All rights reserved.
- Description: C1
- Description: 2003002951
A fully automated CAD system using multi-category feature selection with restricted recombination
- Authors: Ghosh, Ranadhir , Ghosh, Moumita , Yearwood, John , Mukherjee, Subhasis
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at 6th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2007, Melbourne, Victoria : 11th-13th July 2007 p. 106-111
- Full Text:
- Description: In pattern recognition problems features plays an important role for classification results. It is very important which features are used and how many features are used for the classification process. Most of the real life classification problem uses different category of features. It is desirable to find the optimal combination of features that improves the performance of the classifier. There exists different selection framework that selects the features. Mostly do not incorporate the impact of one category of features on another. Even if they incorporate, they produce conflict between the categories. In this paper we proposed a restricted crossover selection framework which incorporate the impact of different categories on each other, as well as it restricts the search within the category which searching in the global region of the search space. The results obtained by the proposed framework are promising.
- Description: 2003005429