Introduction to Seminar Topic Encryption for Image Security:

Conventionally encryption of the image was done by cryptography. The drawbacks of cryptography is mainly that it is slow and its inability to factorize large numbers. Chaos based encryption have exhibited advanced features and the algorithm involved in the process is mainly based on rearranging the pixels.


The history of chaos can be traced back to early 1970s, which exhibits a property known as ‘butterfly effect’.  The property of chaos is that though it is unpredictable and non-linear but it can be used as pseudo number generator.


It is also known as Arnold’s Cat Map. In this the original organization of pixels is randomized. Extensively Cat map transformations can be made. While recovering an image through continuous iterations image can be retrieved in its original form. Treating Cat map as chaos can also result in magnification of small errors into large form.

Encryption and decryption

The encryption of data is a form of converting it into cipher text which protects the information and when the data reaches its target it can converted back to its original form by decryption. This is utilized by cryptography anddepends mainly on length of the key and algorithm. The objective of this method is to achieve confidentiality, authenticity, integrity, nonrepudiation. There are two types of cipher used namely substitution and transposition ensuring data encryption standards.


Simplified data encryption utilizes permutation and substitution. The analysis is made complex when we alternate the linear maps with the non-linear maps.

Chaos and cryptosystem

When comparing the two, cryptosystem requires mixing, sensitivity and dependency on control parameters.  Another observation is that the latter work on finite system.

Formulation of algorithm

This is accomplished by confusion and diffusion that modifies the pixel value.


Chaotic Cat map can be used as secured form of encryption method.

d.  The enhancement of the algorithm would be to add texture while classifying the segments. The experiments also conclude that a variety of images with peculiar features will enable us to setup an assessable image retrieval system.

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