Abstract
In computer vision, scene text component recognition is an important problem in end-to-end scene text reading systems. It involves two major sub-problems - segmentation of such components into scene characters and classification of segmented characters into known character classes. Significant attention and increasingly focused research efforts are being put forth and reasonable progress in this field has already been made, though a diversity of challenges like background complexity, variety of text appearances, noise, blur, distortion and various other degradation and deformation issues are still left to address. In this paper, we present (i) a detail survey of scene component segmentation and/or recognition methods reported so far in literature, (ii) related datasets available for quantitative evaluation and benchmarking segmentation and/or recognition performance, (iii) comparative results and analysis over the reported methods, and (iv) discussion on open areas to be looked into in order to achieve the desired goal of end-to-end scene text recognition. Moreover, this paper provides an acceptable reference for researcher in the area of scene text components segmentation and recognition.
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