Text detection in images

author: Natalia Vassilieva, HP Labs
published: Oct. 8, 2013,   recorded: August 2012,   views: 4613

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


Text detection in images is an important component for a wide range of applications. The most obvious one is Optical Character Recognition (OCR). It can be used to digitize the content of paper documents, to automate the annotation and indexing of multimedia documents, to provide computerized aid for visually impaired, and for many other purposes. Common OCR tools being designed to detect and recognize paragraphs of text perform well on scanned documents, but fail to recognize text in drawings, charts and images of natural scenes when applied to the whole image. Other algorithms for text detection are required for these types of images. This talk will address key approaches to a problem of text detection for various types of images and showcase text detection for charts and screenshots. We will discuss script dependency of the approaches under study: which of them are capable of performing equally well for Latin, Cyrillic or Chinese?

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: