Abstract
The Robust Reading research area deals with detection and recognition of textual information in scene images. In particular, natural scene text detection and recognition techniques have gained much attention from the computer vision community due to their contribution to multiple applications. Common text detection and recognition methods are often affected by environment aspects, image acquisition problems, and the text content. In this work, a method for text detection and recognition in natural scenes is proposed. The method consists of three stages: 1) phase-based text segmentation, obtained by applying the MSER algorithm to the local phase image; 2) text localization, where segmented regions are classified and grouped as text and non-text components; and, 3) word recognition, where characters are recognized utilizing Histograms of Phase Congruency. Experimental results are presented using a known dataset and evaluated under precision and recall measures.
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