M. James Stephen

Simple League Championship Algorithm

is a lot of discussion in the literature on the advantages of one soft computing technique over the other. Number of new meta heuristic algorithms are made available for solving different optimization problems. But always there is some ambiguity in deciding which technique is better than the other to solve a specific optimization problem in a particular context. A new methodology has been proposed in this paper which provides some theoretical frame work to use multiple optimization techniques at the same time onto a single optimization problem. This new approach has been implemented to solve image enhancement problem in a fingerprint. First the methodology of this new approach has been described then the application of the proposed methodology is presented with some experimental results.

Towards Accurate Estimation of Fingerprint Ridge Orientation Using BPNN and Ternarization

Accurate estimation of ridge orientation is a crucial step in fingerprint image enhancement because the performance of a minutiae extraction algorithm and matching heavily relies on the quality of the input fingerprint images, which in turn relies on proper estimation of ridge orientation. When ridge structure is not clear in a noisy fingerprint image, ridge orientation estimation becomes tough and it is considered as one of the most challenging tasks in fingerprint image enhancement process. A new methodology based on neural network approach and Ternarization for ridge orientation estimation is proposed in this paper. In the present work a trained Back Propagation Neural Network (BPNN) is used for accurate ridge orientation. The advantage with the Ternarization process is that it eradicates the false ridge orientation for which the neural network wrongly responds with the larger value and at the same time, it keeps the correct ridge orientation blocks intact without making them blur. This helps in qualitative extraction of minutiae points from the fingerprint image. The experimental results have shown that the proposed method for estimating ridge orientation works far better than the traditional gradient based approach.

Removal of False Minutiae with Fuzzy Rules from the Extracted Minutiae of Fingerprint Image

Human fingerprints are rich in details called minutiae, which can be used as identification marks for fingerprint verification. Minutiae are the two most prominent and well-accepted classes of fingerprint features arising from local ridge discontinuities: ridge endings and ridge bifurcations. In today’s world minutia matching is most popular and modern technology for fingerprint matching. .If there is enough minutia point in one fingerprint image that are corresponding to other fingerprint image, then it is most likely that both images are from the same finger print. In this paper, we proposed a complete system for minutiae extraction and removing the false minutiae from the extracted ones.

Enhancing Fingerprint Image through Ridge Orientation with Neural Network Approach and Ternarization for Effective Minutiae Extraction

Among the various biometric identifications available, fingerprints authentication is the oldest and the most reliable source of authentication. Identification of fingerprints basically relies on minutiae extraction. In most cases the finger print images that are obtained are of poor quality due to various reasons such as scars, dirt, non-uniform ink intensity and skin diversities. So enhancement of image prior to extraction increases the consistency. In this paper a new methodology was proposed for finger print image enhancement where the process begins with ridge orientation using neural network approach that follows dividing the image into white block, black block and grey block, which is called ternarisation, which is a new methodology to deal with uncertainty of minutiae. Then the image is binarised using the concept of pixel aggregation. And finally thinning is applied before proceeding to effective minutiae extraction.

More Secured Text Transmission with Dual Phase Message Morphing Algorithm

In this global village, where with the advancements in the field of communications, ensuring security to the data being transmitted has become very vital. These safety and security issues contributed to the outgrowth of secret communication. While encryption simply encodes the data making it difficult for the layman to understand, Steganography deals with hiding data within another data making them unaware of it. Both concepts ensure data security but in different forms. These two approaches when unified provide much better security to the data than that provided by either of encryption or Steganography.

Deploying Access Control using Extended XACML in Open Web Service Environment

Now a days web services have a greater role in development of software systems. Generally, web server wants to determine which access can be granted and communicate with requesterfor open web service environment. These systems are designed to be open and web servers does not have determined conditions for communicate to the access requester. Such consideration makes traditional access control not applicable, which depends upon requester identification and authentication. Typically, XACML language is proposed for define the access control policy. It does not support novel features and not suitable in practice. In this paper, we extend the current XACML by providing novel features for controlling access in interoperable and flexible way, and then illustrate how such concepts can be deployed. Also, extend the standard XACML architecture to incorporate the new features for open web service systems