http://localhost:8080/xmlui/handle/123456789/2252 2026-06-23T06:32:29Z 2026-06-23T06:32:29Z Ugale, Sunita Pandit Mishra, Vivekanand Amphawan, Angela http://localhost:8080/xmlui/handle/123456789/2325 2019-08-15T04:58:02Z 2013-04-01T00:00:00Z

Title: Ultra Long Period Reversible Fiber Gratings as a Pressure Sensor Authors: Ugale, Sunita Pandit; Mishra, Vivekanand; Amphawan, Angela Abstract: We report here for the first time the fabrication and characterization of mechanically induced ultralong period fiber gratings (MULPFG) with period size up to several millimeters. In these gratings the coupling of the fundamental guided core mode takes place with cladding modes of high diffraction orders. The transmission characteristic of grating with different external applied pressure has been experimentally verified

2013-04-01T00:00:00Z Kesharwani, Neha Ugale, S.P. http://localhost:8080/xmlui/handle/123456789/2283 2019-08-14T05:38:18Z 2014-06-01T00:00:00Z

Title: Fingerprint Recognition Using Level 3 Features Authors: Kesharwani, Neha; Ugale, S.P. Abstract: Fingerprints are a great source for identification of individuals. It is one of the oldest form of biometric identification. Fingerprint friction ridge details are generally described in a hierarchical order at three different levels,namely,Level1(pattern),Level2(minutia points),and Level 3(Pores and ridges contour) Although latent print examiners frequently take advantage of Level 3 features to assist in identification, Automated Fingerprint Identification Systems (AFIS) currently rely only on Level 1 and Level 2 features. Level 3 features carry significant discriminatory information. In our project we have presented an automated Fingerprint recognition system which uses level 3 features in combination with level 2 features which makes a matching system more accurate, efficient and beneficial.

2014-06-01T00:00:00Z Bhabad, Sanjivani S. Naidu, Kamaraj http://localhost:8080/xmlui/handle/123456789/2279 2019-08-14T05:00:22Z 2014-11-11T00:00:00Z

Title: RASTA-PLP For Speech Recognition of Articulatory Handicapped People Authors: Bhabad, Sanjivani S.; Naidu, Kamaraj Abstract: This paper describes an approach of isolated word recognition for normal people and articulatory handicapped people using relative spectral and cepstral perceptual linear predictive (RASTA-PLP) feature extraction techniques. Recognition is carried out using a minimum distance classifier. The results of RASTA-PLP Cepstral coefficients and RASTA-PLP spectral coefficients are compared. The result for normal persons shows that the recognition accuracy is 75.11% from features of RASTA-PLP Cepstral coefficients as compared to 62.11% calculated from RASTA-PLP spectral coefficients. The result for articulatory handicapped persons shows that the recognition accuracy is 45.60% from features of RASTA-PLP Cepstral coefficients as compared to 38.50% calculated from RASTA-PLP spectral coefficients.

2014-11-11T00:00:00Z Sotane, Manisha jagtap, kishori http://localhost:8080/xmlui/handle/123456789/2278 2019-08-14T04:53:42Z 2014-06-12T00:00:00Z

Title: Biometric Solution for Person Identification Using Iris Recognition System Authors: Sotane, Manisha; jagtap, kishori Abstract: The features extracted from the human iris can identify individuals even among genetically identical twins. A human iris is fully formed six months after birth and is invariant to physical changes, such as illness or pregnancy, as is the retina (e.g., diabetic retinopathy). As a central component of the Iris recognition system, we present an iris analysis technique that aims to extract and compress the unique features of a given iris with a discrimination criterion using limited storage. The compressed features should be at maximal distance with respect to a reference iris image database. The iris analysis algorithm performs several steps such as the algorithm detects the human iris by using a new model which is able to compensate for the noise introduced by the surrounding eyelashes and eyelids, it converts the isolated iris using a wavelet transform into a standard domain where the common radial patterns of the human iris are concisely represented, and It optimally selects, aligns, and near-optimally compresses the most distinctive transform coefficients for each individual user.

2014-06-12T00:00:00Z