A PERTURBATION­BASED APPROACH FOR MULTI­CLASSIFIER SYSTEM DESIGN

Microsoft, Motorola, Siemens, Hitachi, IAPR, NICI, IUF This paper presents a perturbation­based approach useful to select the best combination method for a multi­classifier system. The basic idea is to simulate small variations in the performance of the set of classifiers and to evaluate to what extent they influence the performance of the combined classifier. In the experimental phase, the Behavioural Knowledge Space and the Dempster­Shafer combination methods have been considered. The experimental results, carried out in the field of hand­written numeral recognition, demonstrate the effectiveness of the new approach

ZONING DESIGN FOR HAND­WRITTEN NUMERAL RECOGNITION

Microsoft, Motorola, Siemens, Hitachi, IAPR, NICI, IUF In the field of Optical Character Recognition (OCR), zoning is used to extract topological information from patterns. In this paper zoning is considered as the result of an optimisation problem and a new technique is presented for automatic zoning. More precisely, local analysis of feature distribution based on Shannon's entropy estimation is performed to determine "core" zones of patterns. An iterative region­growing procedure is applied on the "core" zones to determine the final zoning

Increasing the Number of Classifiers in Multi-classifier Systems: A Complementarity-Based Analysis

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