Text Recognition in Natural Images : A study in Text Detection

Abstract: In recent years, a surge in computer vision methods and solutions has been developed to solve the computer vision problem. By combining different methods from different areas of computer vision, computer scientists have been able to develop more advanced and sophisticated models to solve these problems. This report will cover two categories, text detection and text recognition. These areas will be defined, described, and analyzed in the result and discussion chapter. This report will cover an exciting and challenging topic, text recognition in natural images. It set out to assess the improvement of OCR accuracy after three image segmentation methods have been applied to images. The methods used are Maximally stable extremal regions and geometric filtering based on geometric properties. The result showed that the accuracy of OCR with segmentation methods had an overall better accuracy when compared to OCR without segmentation methods. Also, it was shown that images with horizontal text orientation had better accuracy when applying OCR with segmentation methods compared to images with multi-oriented text orientation.