Tata Consultancy Services Limited

Bala Mallikarjunarao Garlapati

Srinivasa Rao Chalamala

Krishna Rao Kakkirala

Arun Kumar Jindal

Ajeet Kumar Singh

Balakrishna Gudla

Santosh Kumar Jami

Sachin Premsukh Lodha

Sunil Kumar Kopparapu

Vijayanand Mahadeo Banahatti

Bhavikkumar Bhagvanbhai Vachhani

Imran Ahamad Sheikh

Biometric templates (template) are used to store biometric data of one or more users. As biometric data of each user is unique and non-replaceable, template security is a major concern. This disclosure relates generally to template protection, and more particularly to a method and system for biometric template protection. The system generates a final perturbation value for data in the template, based on a first binary code (BC), a second binary code (BC'), feature vectors corresponding to data in the template, and an initial random perturbation. The final perturbation and the feature vectors are mapped to the first binary code. The first binary code represents the template. Every time the first binary code is compromised, the value of first binary code is updated, and the whole process is repeated to generate corresponding final perturbation and then the mapping is done.

Method and system for biometric template protection

This disclosure relates generally to a method and system for muting of classified information from an audio using a fuzzy approach. The method comprises converting the received audio signal into text using a speech recognition engine to identify a plurality of classified words from the text to obtain a first set of parameters. Further, a plurality of subwords associated with each classified word are identified to obtain a second set of parameters associated with each subword of corresponding classified word. A relative score is computed for each subword associated with the classified word based on a plurality of similar pairs for the corresponding classified word. A fuzzy muting function is generated using the first set of parameters, the second set of parameters and the relative score associated with each subword. The plurality of subwords associated with each classified word is muted in accordance with the generated fuzzy muting function.

Method and system for muting classified information from an audio

Systems and methods for insertion of a watermark into images and tampering detection of the watermarked images by a Convolutional Neural Network (CNN) technique. The traditional systems and methods provide for detecting the tampering of the watermarked images by simply identifying a presence of an inserted watermark into an image but none them provide for inserting a random sequence into input image(s) and then detect the tampering by classifying the input image(s) by a neural network. Embodiments of the present disclosure provide for insertion of the watermark into the input image(s) and tampering detection of the watermarked images by training a Convolutional Neural Network (CNN)to classify the images as tampered or non-tampered, extracting random noise, obtaining non-classified watermarked images from the random noise, and obtaining, from the non-classified watermarked images, classified watermarked images and detecting an absence or a presence of the tampering based upon the classified watermarked images.

Neural network based insertion of watermark into images and tampering detection thereof

System and method for text localization in images are disclosed. In an embodiment, a line and graphic eliminated image is received. Further, horizontal projection is performed on rows of the image to obtain a first flag vector, the flag vector indicates whether there is text in each row. Furthermore, a number of run-lengths of consecutive 1's and 0's is computed in the first flag vector. Moreover, text lines is extracted in the image based on the computed number of run-lengths of consecutive 1's and 0's in the first flag vector. Also, vertical projection is performed on the text lines to obtain a second flag vector for the text lines. Further, a number of run-lengths of consecutive 1's and 0's is computed in the second flag vectors. Furthermore, text is localized in the image based on the computed number of run-lengths of consecutive 1's and 0's in the second flag vectors.

System and method for text localization in images

System(s) and method(s) for embedding and extracting a watermark from a digital media are described. The method may include embedding a set of watermark bits in a N*N block of the digital media based on a local binary pattern (LBP) synthesis process. The LBP synthesis process comprises changing a value of a neighbor of a central pixel of the N*N block to make the value of the neighbor greater than a value of the central pixel when a watermark bit corresponding to the neighbor is '1' and changing the value of the neighbor of the central pixel to make the value of the neighbor lesser than the value of the central pixel when the watermark bit corresponding to the neighbor is '0'.

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Hyderabad Telangana, India

Bala Mallikarjunarao Garlapati