Optimized Solution for Efficient Detection of Text from Images
Keywords:
Pre-processing, Segmentation, Optical Character Recognition (OCR)Abstract
Text detection and recognition in camera captured images have been considered as very important problems in computer vision community. Text detection and recognition is a hot topic for researchers in the field of image processing. Text detection and extraction is performed in a four-step approach that consists of the pre-processing which include binarization and noise removal of an image, image segmentation using connected component analysis, feature extraction using variance generation and finally classification by choosing a threshold value of variance property. The goal of the project is to develop an Android-platform based text detection application that will be able to recognize the text captured by a mobile phone camera. Optical character recognition (OCR) methods recognize the characters and can be really useful when you have got a paper document you want in digital, editable form. Character which can be used to assist a wide variety of applications, such as image understanding, image indexing and search, geolocation or navigation, and human computer interaction. Optical character recognition is very important technique that is used for recognition of characters and it is very useful when we want our paper document in digital form and with the help of this technique we can edit our form.
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