Vikas T. Humbe

Work place: Department of Computer Science, SRTMUN University, Latur, MH, India



Research Interests: Pattern Recognition, Image Processing, Data Structures and Algorithms


Dr. Vikas T. Humbe has completed his Ph.D. degree from University Department of Computer Science and Information Technology, Dr.B.A.M.U. Aurangabad and is working as the Assistant Professor at Department of Computer Science, School of Technology, S.R.T.M. University, Nanded, Sub-campus, Latur. In teaching, he has been focusing on Digital Image and video processing concepts and Problem Based Learning approaches in Computer Science Education. In research, his current interests include Pattern Recognition, Image and video based processing, Data ware housing and web mining etc. Dr. Humbe has published 42 research articles at National/International conferences and journals also he is the author of the books. He is the IEEE Graduate Member and has immense research recognition worldwide.

Author Articles
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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