Shriram D. Raut

Work place: Department of Computer Science and Application, Solapur University, Solapur, MH, India



Research Interests: Theoretical Computer Science, Computer systems and computational processes, Computational Science and Engineering, Applied computer science


Mr. Shriram D. Raut is pursuing his Ph.D. degree in Computer Science, and is research scholar and has completed his M.Sc. degree in Computer Science from University Department of Computer Science and Information Technology from Dr.B.A.M.U. Aurangabad and is working as the Assistant Professor at Department of Computer Science and Application, School of Computational Sciences, Solapur University, Solapur. He worked as the Research Scholar and submitted a project in Computer Science under the UGC SAP (II) DRS Phase-I: 2009-2014 under the theme „Biometric: Multimodal System Developmentā€Ÿ.

Author Articles
An Approach to Boundary Extraction of Palm Lines and Vein Pattern

By Shriram D. Raut V. T. Humbe

DOI:, Pub. Date: 8 Nov. 2014

The palm vein biometrics is automated tool to recognize a person based on human vein pattern. The vein pattern is intrinsic and subcutaneous so that is very difficult to forge or fake. This paper discusses about the feature extraction of the hand based recognition system that involves features like vein pattern, principal lines and secondary lines. The morphological operations such as opening, closing and edge detection technique like canny algorithm are used to extract the feature set. The result shows the prominent feature extraction using image processing techniques.

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Statistical Analysis of Resulting Palm vein Image through Enhancement Operations

By Shriram D. Raut Vikas T. Humbe

DOI:, Pub. Date: 8 Dec. 2013

Nowadays biometric is playing a key role in the field of forensic and commercial applications. The vein biometrics is a robust biometric in recent trends.The vein pattern is very difficult to forge or fake. The traits are not going to be changed from birth to death. This paper discusses image enhancement operations and its result when applied on multispectral palm vein image. The image enhancement operations are much helpful to extract the vein patternas features.The experiments can be used to highlight or trace a vein pattern lies at palm region of hand. The proposed work gains vein pattern and considered as the stepping stone towards feature extraction. The paperalso discusses the comparison of statistical properties such as mean, standard deviation and coefficient of original image and images resulting out through enhancement operations. The enhancement operation is a key to gain the vein pattern. The image analysis can be framed well usingstatistical image measurements.

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Biometric Palm Prints Feature Matching for Person Identification

By Shriram D. Raut Vikas T. Humbe

DOI:, Pub. Date: 8 Nov. 2012

Biometrics is playing an important role for person recognition. The Biometrics identification of an individual is can be done by physiological or behavioral characteristics; where the palm print of an individual can be captured by using sensors and is one of among physiological characteristics of an individual. Palm print is a unique and reliable biometric characteristic with high usability. A palm print refers to an image acquired of the palm region of the hand. The biometric use of palm prints uses ridge patterns to identify an individual. Palm print recognition system is most promising to recognize an individual based on statistical properties of palm print image. It is rich in its features: principal lines, wrinkles, ridges, singular points and minutiae points. This paper proposes a Biometric Palm print lines extraction using image processing morphological operation. The proposed work discusses the significance; since both the palm print and hand shape images are proposed to extract from the single hand image acquired from a sensor. The basic statistical properties can be computed and are useful for biometric recognition of individual. This result and analysis will result into Total Success Rate (TSR) of experiment is 100%. This paper discusses proposed work for biometric recognition of individual by using basic statistical properties of palm print image. The experiment is carried out by using MATLAB software image processing toolbox.

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