Analysis of Text-Based CAPTCHA Images using
Template Matching Correlation Technique
Abstract:-
Text-based CAPTCHA images have been widely utilized in on-line applications to anti malicious programs which attempt to make failure in execution or computation. Although installing CAPTCHA enhances system’s security, it has to be continuously analyzed, improved and developed for hard decoding or extracting from intrusion of automatic programs. This paper is mainly focused on examination of text-based CAPTCHA images with several degrees of noise, skew, font type and size. The
Template Matching Correlation (TMC) technique consisting of image conversion, threshold, noise rejection, segmentation and recognition methods, is introduced for analysis. From simulation results, the robustness is increased after the image is distorted by noise background and font skew. The basic idea of CAPTCHA is to resist exertion of decoding by segmentation and character recognition algorithms. The preliminary version of CAPTCHA arranges incoherently a word image from a dictionary and then includes distorted and noise image background. Afterwards, a user is asked to decode and to verify the word appearing in the image. The method, algorithm and implementation are introduced. From the simulation results based on the acceptable robustness and the human reading ability (normalized recognition) in the range. To introduce an efficient computation method to come out a suitable threshold value to enhance the efficiency of noise rejection and to improve the
Performance of segmentation.
Existing System:-
Ø Graphic-based utilizes the disadvantage of pattern recognition which is difficult to execute the comparison process with graphic information for design and
Implementation.
Ø Text-based is designed not only for simple to use but also for reducing time-consuming where many researches are playing attention on this area.
Ø The technique used multiple noise images, where invisible objects or texts were hidden within a certain area.
Ø There are several methods for conversion and matching such as maximum method, average method and weight average method.
Proposed System:-
Ø The CAPTCHA image utilizes a simple color scheme to increase its usability to avoid the potentially complicated consequences of usability and security.
Ø The algorithm was mainly developed for robust analysis, based on segmentation and recognition characters depending on image’s features.
Ø The algorithm was mainly developed for robust analysis, based on segmentation and recognition characters depending on image’s features, the segmentation process will be repeated again.
Ø The function finds and counts the number of groups of continuous pixels, and then calculate their position in row and column which are used for separation.
Hardware Requirements:-
ØSYSTEM : Pentium IV 2.4 GHz
ØHARD DISK : 40 GB
ØRAM : 256 MB
Software Requirements:-
ØOperating System : Windows 7
ØIDE : Microsoft Visual Studio 2010
ØCoding Language : C#.NET.