A Review on Text Detection from Multi-Oriented Text Images in Different Approaches

Text extraction plays a major role in finding valuable information from images. This paper discusses various techniques such as image processing, data mining, machine learning or neural network techniques used in the process for extracting text in multi-oriented images and a comparative study on them. The task of detecting text in images depends upon several factors like font styles, text size, colour, background, orientation. This paper additionally offers overall performance comparison of numerous present techniques used by an analyst for taking textual content from images and the overall performance of our method is evaluated using different datasets. The experimental outcomes depict the overall performance of the technique based on parameters like recall, precision and accuracy.