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

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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:-

Graphic-based utilizes the disadvantage of pattern recognition which is difficult

to execute the comparison process with graphic information for design and

Implementation.

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.

The technique used multiple noise images, where invisible objects or texts were

hidden within a certain area.

There are several methods for conversion and matching such as maximum

method, average method and weight average method.

Proposed System:-

The CAPTCHA image utilizes a simple color scheme to increase its usability to

avoid the potentially complicated consequences of usability and security.

The algorithm was mainly developed for robust analysis, based on segmentation

and recognition characters depending on image’s features.

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.

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:-

SYSTEM : Pentium IV 2.4 GHz

HARD DISK : 40 GB

RAM : 256 MB

Software Requirements:-

Operating System : Windows 7

IDE : Microsoft Visual Studio 2010

Coding Language : C#.NET.