Abstract
Images contain various types of useful information that should be extracted whenever required. A various algorithms and methods are proposed to extract text from the given image, and by using that user will be able to access the text from any image. Variations in text may occur because of differences in size, style,orientation, alignment of text, and low image contrast, composite backgrounds make the problem during extraction of text. If we develop an application that extracts and recognizes those texts accurately in real time, then it can be applied to many important applications like document analysis, vehicle license plate extraction, text- based image indexing, etc and many applications have become realities in recent years. To overcome the above problems we develop such application that will convert the image into text by using algorithms, such as bounding box, HSV model, blob analysis,template matching, template generation.
Highlights
Handwritten text from image has been a subject of study and research for many years
We use different algorithms to improve the accuracy of the existing system. In this method to improve readability of text documents through manually enhancing text strokes is proposed [1]. We develop such application that will convert the image into text by using algorithms, such as bounding box, HSV model,blob analysis, template matching, and template generation
In proposed system,we are using different algorithms to improve the accuracy of the text document or text image[16].It uses the image as input can be captured by laptop camera
Summary
Handwritten text from image has been a subject of study and research for many years. There are different methods currently employed to improve the visibility of text in text documents. We use different algorithms to improve the accuracy of the existing system. In this method to improve readability of text documents through manually enhancing text strokes is proposed [1]. We develop such application that will convert the image into text by using algorithms, such as bounding box, HSV model,blob analysis, template matching, and template generation. To develop an interface to train the application for understands the difficult and unreadable handwritingCollect handwritten characters, symbols as an input data and train the application. Give handwritten character input as an image and extract the character. Connected component analysis was used to locate blobs that were about the size of characters.The characters were manually identified and Stored in the database [2]
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