Optical character extraction under different illumination conditions

Abstract:

There are a variety of lighting scenarios that may be used to take an image. Consequently, if the text pictures are shot using a variety of lighting effects. When seen in picture format, the words cannot be read. In this paper, we suggested a system that is capable of extracting text from images of recorded text in MATLAB by employing optical character extraction regardless of the lighting conditions.

In this section, we will extract text from images using several image processing technologies. The primary objective is to recognize the characters in each of the different lighting scenarios. Text will be on the paper that is printed. The picture of the printed paper will be captured by us. In order to extract characters from printed paper, we make use of an efficient method.

This system reads the text and analyzes each line in turn as it moves through it. In this section, we will put this system into operation by utilizing the calculation program MATLAB together with its image processing toolbox. The image processing toolkit will be used by the system to extract words from images. whilst an image is being taken by a camera or a webcam.

This means that the image is more susceptible to noise and other forms of environmental disturbance. The thresholding approach will be utilized by us in order to successfully extract text from images. The application of image pre-processing stages takes place with pictures. Things that aren’t wanted are taken away. The retrieved text is given bounding boxes after being processed. The text is presented here in an image format. These pictures are turned into character representations.

The system extracts characters from images by using something called optical character recognition. The directory is where the character and number pictures are kept. The bounding box has been used to divide the retrieved text and picture. Each character and each number will be contained within their own bounding boxes.

Each letter, number, and digit is shrunk to fit the picture that is saved in the directory. A comparison is made between the extracted picture and the existing character image feature. Characters are identified once the comparison is made.

At long last, characters that have been discovered are presented in text format. In order to extract text from images, optical character extraction is the method of choice. In this section, we are going to extract text from images regardless of the lighting.

Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.