Latent fingerprint has become more popular and attracted among the researchers in the recent days and it has been used widely in security such as India’s Aadhaar project, Department of Homeland Security’s US-VISIT program, the UK Border Agency, law enforcement and forensic applications. There have been different biometric traits that were used for matching to identify the person. While investigation a small number of accesses are recognized in latent fingerprint images because the fingerprint has own individuality. Latent fingerprint has been consisting some challenges in term of poor quality images, unclear texture and nonlinear distortion, appropriate matching algorithm and publicly available latent fingerprint database. Consequently, the study has considered and talked about different accessible strategies and methods that have been utilized as a part of the past exploration concentrates on furthermore gives the bearing to further research in the different field of inactive unique finger impression application.

A latent fingerprint is an interesting issue because of it has attained from crime places and moreover contained a low quality image, less number of features and unwanted noises. It is necessity to extract the original image with exact boundary from the surface for further processing such as authentication, identification and matching. In this work, a new distance measure has been proposed for latent fingerprint edge detection using Intuitionistic Type-2 Fuzzy Entropy IT2FE and a comprehensible definition is made for Intuitionistic Type-2 Fuzzy Sets IT2FS. IT2FS takes into account of uncertainty in the form of membership function which is also termed as Intuitionistic Type-2 Fuzzy Divergence IT2FD. The experiment is conducted with public domain fingerprint databases such as FVC-2004 and IIIT-latent fingerprint. The edge detection is carried out with the proposed method and the results are discovered better regarding existing method.

In this paper, we present aweighted arithmetic average operator based on intervalvalued intuitionistic fuzzy values and their application to multi criteria decision making for investment. Based on the scoring value method of interval-valued intuitionistic fuzzy values of the decision-maker with respect to alternatives

Fuzzy sets are a major simplification and wing of classical sets. The extended concept of set theory is rough set (RS) theory. It is a formalistic theory based upon a foundational study of the logical features of the fundamental system. The RS theory provides a new mathematical method for insufficient understanding. It enables the creation of sets of verdict rules from data in a presentable manner. An RS boundary area can be created using the algebraic operators union and intersection, which is known as an approximation. In terms of data uncertainty, fuzzy set theory and RS theory are both applicable. In general, as a uniting theme that unites diverse areas of modern arithmetic, symmetry is immensely important and helpful. The goal of this article is to present the notion of rough fuzzy ideals (RFI) in the gamma ring structure. We introduce the basic concept of RFI, and the theorems are proven for their characteristic function. After that, we explain the operations on RFI, and related theorems are given. Additionally, we prove some theorems on rough fuzzy prime ideals. Furthermore, using the concept of rough gamma endomorphism, we propose some theorems on the morphism properties of RFI in the gamma ring.

In this paper, we propose a Multiparty Identification Scheme based on Nearring root Extraction Problem. This scheme enables more than two or three parties to prove their identity among themselves. We have chosen Nearring root extraction problem as a basis for our scheme. An adversary finds difficult to break the scheme as he/she finds very hard to extract the nth root for a given near polynomial ring.