An Examination of Pattern Matching-Based Image-Based Text Segmentation and Recognition

Abstract

Text in photos contains significant and more valuable information that can be utilized to analyze and describe images. Text is therefore the most significant content in photographs. Thus, it is essential to separate and recognize text from images. This process is used in a variety of applications, such as archive recovery, object ID, vehicle tag position, flexible robot route, and so forth.  Division is the process of breaking apart an article or image into multiple pieces based on the requirements of the application. It can be completed using a variety of techniques. Optical character recognition (OCR) is a technique for text recognition from images. It consists of a PC framework designed to convert images of written or printed text captured by scanners into machine-editable text. This research considers several approaches for text recognition and identification from varied images.