Font and function word identification in document recognition
Computer Vision and Image Understanding
Rotation Invariant Texture Features and Their Use in Automatic Script Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Font Recognition Based on Global Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Machine Printed Text and Handwriting Identification in Noisy Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture for Script Identification
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Human beings are capable of distinguishing a variety of texture almost at a glance. By modelling the mechanism, we will realize a flexible texture analysis. We propose a new technique inspired by such human early-vision ability to distinguish handwritten character regions from machine-printed regions in document images. In the technique, we evaluate the two-dimensional power spectrum to extract feature values that reflects fluctuations unavoidable in handwritten characters. Experiments show that a certain feature value of handwritten characters is often larger than that of machine-printed characters. We generated a map obtained by superimposing the feature value on the document image. The map showed that our proposed method is useful to distinguish handwritten character regions from machine-printed character ones.