Abstract

A large amount of data are input into the computer. These data can be presented as visual images, sounds (speech), electronic signals, etc. And there is a problem with their recognition. Recognition of graphic symbol, including letters and numbers is the most common one. There are three basic methods of graphic symbols identification: reference, structural and feature ones. For example, programs like FineReader, Readiris, ScanSoft, OmniPage, CuneiForm can be used to recognize the graphic symbols, which are entered into the computer. Significant reliance recognition accuracy of image quality and some distortion of primary image are main disadvantages of these programs and methods We can use fuzzy logic or neural network algorithms to improve recognition accuracy.For example neural networks are used in Google technology. We offered the use of numbers recognition system based on fuzzy logic to improve the accuracy and the feature method was proposed. As informative parameters, i.e. recognition features, two positive and two negative transitions were chosen. Transition is defined as the difference between the current local maximum (or minimum) and the previous local minimum (or maximum) number of pixels (intensity) which include images. The number of pixels is counted within vertical sectors into which the number of images is divided and the width of these sectors may vary from 1 to 3 pixels. Another informative parameter is the number of transitions counted in the separation of the image number into the horizontal sectors. Using of Fuzzy Logic Designer in LabVIEW for design and realization of the fuzzy logic system is considered in the article. The recognition system was designed as a software component in package LabVIEW. The research of the developed recognition system in terms of distortion of numbers images by their rotation was held. The angle of this turn may vary from 0 to 10 both clockwise and counterclockwise. By turning clockwise the range of rotation angle is 2-4 times larger than counterclockwise turn. This depends on the width of the sector, which can vary from 1 to 3 pixels. By turning clockwise the range of distortion is narrowed to 1.5 times when the width of sector increases. In the future we plan to optimize the system to increase the allowable angle of image rotation and research the impact of distortion in the form of the geometric size changes.

Authors and Affiliations