Multi-script robust reading competition in ICDAR 2013

Abstract

A competition was organized by the authors to detect text from scene images. The motivation was to look for script-independent algorithms that detect the text and extract it from the scene images, which may be applied directly to an unknown script. The competition had four distinct tasks: (i) text localization and (ii) segmentation from scene images containing one or more of Kannada, Tamil, Hindi, Chinese and English words. (iii) English and (iv) Kannada word recognition task from scene word images. There were totally four submissions for the text localization and segmentation tasks. For the other two tasks, we have evaluated two algorithms, namely nonlinear enhancement and selection of plane and midline analysis and propagation of segmentation, already published by us. A complete picture on the position of an algorithm is discussed and suggestions are provided to improve the quality of the algorithms. Graphical depiction of f-score of individual images in the form of benchmark values is proposed to show the strength of an algorithm.