Proving the identity of the individual today is an urgent need in many areas, including social security, financial, criminal and other fields. Biometrics is interested in identifying individuals through personality traits, eye color, fingerprints, height, facial appearance, and signature. Image processing technology supports most of the techniques used in biometrics, by improving images and matching images, to identify the individual identity. Fingerprint recognition is some of the most well-known biometrics, and it the best the used biometric result for confirmation on computer systems. Technic fingerprinting has a great popularity for simplicity of acquisition, the use and approval when compared to other systems. Fingerprint Recognition System consists of four steps: firstly, Image acquisition (image fingerprint) through sensors .Secondly, processing the image so that it obscures the noise that exists, clarifying the hills. Thirdly, Extracting features of injury fingerprints. Fourth, compare the acquired features with features of fingerprint fingerprints in databases. The aim of this paper is to present the latest research in the applications of fingerprint recognition systems.

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Fingerprint pattern knowledge is largely applied in many fields such as access control and identity administration. This is however associated with some problem of automatic fingerprint recognition and therefore this has rendered to the use of the most known method that is biometric identification. Every finger of the hand shows a different pattern of ridges and depression different from the other finger and this pattern remains sole and constant thus helping in identity since fingerprint pattern from one person is different to that of another person. This pattern may alter whenever there are cuts and bruises in the outer part of the finger. Fingerprint pattern recognition method includes the following steps: firstly, matching of the fingerprint which includes the pattern based method and the minutiae method. Secondly, the used algorithm in the recognition and comparing of the fingerprint images. Thirdly, the image enhancement process that helps to improve the quality of the fingerprint pattern and forth the reduction of the size of the image which includes identification of the region of small minutiae and actual minutiae. The objective of this research is recognition of the fingerprint pattern.

Cervical Cancer (CC), sexually transmitted diseases, and cervicovaginal microbiota. In this Sees and Surveys, we center on a few themes in connection to the uterine cervix and barrenness: early cervical cancer and richness saving surgery, cesarean scar deformity, cervical inadequacy, and cervical Mullerian peculiarities. the case of cervix woman cancer proposed in this work revelation and classification system using the modern convolutional updated neural frameworks (CNNs). The cell pictures are fed into a CNNs appear to remove deep- classic algorithm learned highlights. At that point, an extraordinary learning machine (ELM)-based classifier classifies the input pictures. CNNs appear is utilized through trade learning updated algorithm and fine calculate method tuning. Choices to the ELM, multi-layer and perceptron algorithm (MLP) and auto en-algorithm-coder (AE)-based classifiers are in addition work with investigated.