METHOD FOR RECOGNIZING TEXT DATA IN IMAGES

Abstract

The purpose of the study is to study the problems arising in the process of digital image
processing in systems for obtaining textual characteristics of product objects. Such as the selection
of objects that fall into the frames of the video stream and the recognition of text markings,
without the use of specialized hardware. In particular, the problems that arise when working
with images containing different levels of noise and distortion. The objectives of the study i nclude
a comparative and analytical examination of diverse methods and algorithms utilized in
the realm of digital image processing. The primary objectives include identifying, segmenting,
and classifying text-containing portions within the video stream. The study aims to construct a
mathematical model for text extraction from video frames that is adaptable to a wide array of
objects. Evaluate recognition accuracy under varying levels of noise and perform a comparative
analysis against alternative solutions based on the acquired data. The presented system
analyzes the frames of the video stream and classifies the characteristics of the products in the
frame. The solution demonstrates the behaviour and capabilities of digital image processing
methods in various conditions in relation to the tasks of text classification and object search in
a video stream. During the development of this system, a comparison of various options for recognizing
symbolic information was carried out.