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The success gained by applying bit-plane decomposition methods to handwriting recognition have been demonstrated in our previous work [1, 2] . In this paper we address the relationship between the diversity and the improvements obtained by applying multiple combinations of various layers. These layers are obtained by applying a method based on an n-tuple based classification system, namely, the Random Decomposition Technique proposed in  . We investigate 5 combination methods and 9 diversitydoi:10.1109/iwfhr.2004.35 dblp:conf/icfhr/ChindaroSFH04 fatcat:wfrjcf6t3rfinnfbk4eyvsx23a