Text Detection and Recognition in images: A survey
It provides a comprehensive review for researchers in computer vision, but is incremental as it synthesizes existing work without new results.
This paper surveys existing methods for text detection and recognition in images, comparing performance of representative approaches and analyzing remaining problems in the field.
Text Detection and recognition is a one of the important aspect of image processing. This paper analyzes and compares the methods to handle this task. It summarizes the fundamental problems and enumerates factors that need consideration when addressing these problems. Existing techniques are categorized as either stepwise or integrated and sub-problems are highlighted including digit localization, verification, segmentation and recognition. Special issues associated with the enhancement of degraded text and the processing of video text and multi-oriented text are also addressed. The categories and sub-categories of text are illustrated, benchmark datasets are enumerated, and the performance of the most representative approaches is compared. This review also provides a fundamental comparison and analysis of the remaining problems in the field.