Inhaltsangabe:
This book is applicable for the study in Computer Science an Engineering students for UG level and PG level of all Indian Universities. The contains Fingerprint Image Enhancement, Fingerprint Classification Techniques and Basic concept of Fingerprint Feature Extraction, Data Mining Technique. The book describes the design and operation of the architecture, focusing upon the contextual factors influencing the response process, and the way they are measured and assessed to formulate response decisions. The book presents biometrics, automated ways of recognizing an individual based on physiological or behavioural characteristics. Fingerprints are the most widely used biometric feature for identification and authentication. The book determines that there are several efficient methods for fingerprint recognition has ever remained a source of great attraction to many work workers due to their wide application in various fields. It has been observed that most of the existing work is aimed to feature extraction of the fingerprint database based on the minutiae sets, singular points and other techniques. The fingerprint is generally used for personal recognition in the commercial and forensic areas because of its uniqueness, immutability and low cost. Commonly there are two kinds of features of fingerprint recognition local features and global features. The book describes the concept of the fingerprint feature extraction, which aimed to feature extraction of the fingerprint database based on the minutiae sets, singular points and other techniques. The book describes fingerprint classification that assignment every fingerprint to a category in a consistent and reliable method, such that an unknown fingerprint to be searched, has to be compared only to the set of fingerprints within the information belonging to a similar class. The book describes the design and operation of the architecture, focusing upon the contextual factors influencing the response process, and the way they are measured and assessed to formulate response decisions. The architecture is underpinned by the use of response policies which provide a means to reflect the changing needs and characteristics of the organizations. The fingerprint recognition system, which refers to the involuntary technique of validation matching fingerprint images and matching is the last goal of the recognition system to locate the identity of the person. Whose input fingerprint has been submitted, i.e. it evaluates the extracted features or similarities from two fingerprints and determines the possibility that they have been captured from the same finger. The book shows its detail on the aspects of the fingerprint verification is to authenticate the authenticity of one person by his fingerprint, which implies one-to-one comparison. Also, test scenarios are provided, in order to demonstrate how the users in the database for a match. Then the system conducts a one- to – many comparisons to determine an individual’s identification. The book describes reducing the gruelling effort of human experts. The feature extraction and matching of fingerprints are completed and also the output may be displayed. The aim of this book has, therefore this system firstly acquires the fingerprint image. It used the fingerprint database, includes eight fingerprints, i.e., thumb, index, middle, and ring fingers from both hands. In the system using only thumb of each subject is used of both hands and four angles and this process, convert image data to text, numeric code sequence for each fingerprint image This book shows the presented work supported an Apriori algorithmic rule for finding frequent pattern to get association rules then apply class label association rules wherever this algorithm uses FP tree for finding frequent pattern to produce association rules. Apriori algorithmic rule takes longer for big data set wherever FP growth is time efficient to find frequent patterns within the transaction
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