Manickam Adhiyaman

Bio: Manickam Adhiyaman is an academic researcher from VIT University. The author has contributed to research in topics: Minutiae & Fingerprint (computing). The author has an hindex of 4, co-authored 8 publications receiving 41 citations.

Fuzzy Approaches and Analysis in Image Processing

Abstract: Fuzzy set theory originates to a great extent of interest among the researchers in past decades. It is a key tool to handle the imperfect of information in the diverse field. Typically, it plays a very important role in image processing and found the significant development in many active areas such as pattern recognition, neural network, medical imaging, etc. The use of fuzzy set theory is to tackle uncertainty in the form of membership functions when there is an image gray levels or information is lost. This chapter concerns the preliminaries of fuzzy, intuitionistic fuzzy, type-2 fuzzy and intuitionistic type-2 fuzzy set theory and its application in the fingerprint image; furthermore, the contrast enhancement and edge detection are carried out for that with the assistance of fuzzy set theory. It is useful to the students who want to self-study. This chapter composed just to address that issue.

A review study on latent fingerprint recognition techniques

Abstract: 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 impres...

Fingerprint matching and similarity checking system using minutiae based technique

Abstract: Fingerprint matching is one of the most important problems in Automatic Fingerprint Identification System (AFIS). It has emerged as an effective tool for human recognition due to its uniqueness, universality and invariability. The significance of this work is to monitor the matching and similarity for two or more fingerprint images simultaneously. This proposed algorithm has been formulated based on minutiae points which examine n number of images.

Edge Detection Method for Latent Fingerprint Images Using Intuitionistic Type-2 Fuzzy Entropy

Abstract: 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.

Contrast enhancement of fingerprint images using intuitionistic type II fuzzy set

Abstract: A novel contrast image enhancement of fingerprint images using intuitionistic type II fuzzy set theory is recommended in this work. The method of Hamacher T co-norm(S norm) which generates a new membership function with the help of upper and lower membership function of type II fuzzy set. The finger print identification is one of the very few techniques employed in forensic science to aid criminal investigations in daily life, providing access control in financial security;-, visa related services, as well as others. Mostly fingerprint images are poorly illuminated and hardly visible, so it is necessary to enhance the input images. The enhancement is useful for authentication and matching. The fingerprint enhancement is vital for identifying and authenticating people by matching their fingerprints with the stored one in the database. The proposed enhancement of the intuitionistic type II fuzzy set theory results showed that it is more effective, especially, very useful for forensic science operations. The experimental results were compared with non-fuzzy, fuzzy, intuitionistic fuzzy and type II fuzzy methods in which the proposed method offered better results with good quality, less noise and low blur features.

Handbook Of Biometrics

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Social media data analytics for business decision making system to competitive analysis

Abstract: For the past few years, business intelligence has been a major field that uses data analysis to produce key information as part of business decision-making. Data collected from social media sites and blogs are analyzed to make business decisions, a process called social media analytics (SMA). This method, which goes beyond ordinary monitoring or a basic analysis of retweets, develops an in-depth insight into the social consumer. After reading the whole report, add the pertinent figures to the table. Add pertinent data from the Brand24 report to the table. During a social media audit, any followers, impressions, engagement, copy/traffic, and brand mentions are key parameters to analyze. For companies and research institutions, the great interest is to analyse and gain knowledge from user-produced data. These data contain useful knowledge, including customer perceptions feedback and product/service suggestions. Due to content saturation, social media's true meaning regarding business data is hardly ever found. Therefore, in this paper, the business decision making system (BDMS) has been proposed to develop business using social media data analytics. BDMS provides a clear understanding of the key principles, issues and functionality, and big social data developments. Besides, BDMS concentrates on marketing and describes an operational approach for obtaining valuable information from social data. BDMS performs a short and precise description of current use scenarios from the evidence, as per the help of decisions and investment opportunities companies get when using social data analytics. The experimental result shows that BDMS achieves the highest competitive results. With greater accuracy, system dependability, F-1 measurement, and deviation rate of 85.5%, the BDMS system guarantees 93.7%, 86.8%, and 7.0%.

Research on landscape design system based on 3D virtual reality and image processing technology

Abstract: In order to ensure the rationality of landscape design, it is of great practical significance to simulate the planning effect Aiming at the problems of two traditional landscape planning effect simulation systems, a new landscape planning effect simulation system was designed based on virtual reality technology The overall framework of the system is composed of user layer, application layer and display layer According to the system frame structure, hardware such as acquisition equipment, main control equipment, output and display equipment are selected; according to the system framework structure, the system software is designed to run the main program In addition, this paper also based on 3D image processing technology landscape design system In the design process, 3D landscape image can be preprocessed to remove noise information and redundant information, and 3D landscape image feature enhancement method is used to realize 3D landscape image feature enhancement and improve the clarity of landscape design image Combined with the example of garden green space, according to the parametric plant modeling method, the morphological structure parameters of green plants are obtained, and the three-dimensional models of various plant modeling are established; the rules of parametric description of plant spatial layout are adopted, based on the open scene graph rendering engine, and the oculus rift virtual reality equipment is integrated to realize the virtual construction and display of three-dimensional garden vegetation landscape The results show that the design effect of the system is very clear and of good quality It has a high score in the design of courtyard landscape and garden landscape, and the system has low application cost, low energy consumption and high operation efficiency

Piano playing teaching system based on artificial intelligence – design and research

Abstract: In recent years, with the rise of piano teaching, many people began to learn to play the piano. However, the expensive piano teaching cost and its unique teaching model that teachers and students are one to one have caused the shortage of piano education resources, and people learn piano playing has become a luxury activity. The use of computer multimedia software for piano teaching has become a feasible way to alleviate this contradiction. This paper proposes the design of an intelligent piano playing teaching system based on neural network, studies the realization method of the piano teaching system, presents a method of evaluating piano playing by using neural network model for the difficulties in computer piano teaching, that is, computer teaching is one-way knowledge transfer without interaction. In addition, this paper simulates the teacher to guide the students to carry on the playing practice, which is of great significance to the teaching of the piano.