Object Recognition Using Summed Features Classifier

被引：0
作者：
Lindner, Marcus [1 ]
Block, Marco [1 ]
Rojas, Raul [1 ]
机构：
[1] Free Univ Berlin, Inst Informat & Math, D-14195 Berlin, Germany
来源：
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, PT I | 2012年 / 7267卷
关键词：
IMAGE; ALGORITHMS; MODEL;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A common task in the field of document digitization for information retrieval is separating text and non-text elements. In this paper an innovative approach of recognizing patterns is presented. Statistical and structural features in arbitrary number are combined into a rating tree, which is an adapted decision tree. Such a tree is trained for character patterns to distinguish text elements from non-text elements. First experiments in a binarization application have shown promising results in significant reduction of false-positives without producing false-negatives.
引用
收藏
页码：543 / 550
页数：8
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