Signature recognition

About: Signature recognition is a research topic. Over the lifetime, 2138 publications have been published within this topic receiving 37605 citations.

Visual place recognition using HMM sequence matching

Abstract: Visual place recognition and loop closure is critical for the global accuracy of visual Simultaneous Localization and Mapping (SLAM) systems. We present a place recognition algorithm which operates by matching local query image sequences to a database of image sequences. To match sequences, we calculate a matrix of low-resolution, contrast-enhanced image similarity probability values. The optimal sequence alignment, which can be viewed as a discontinuous path through the matrix, is found using a Hidden Markov Model (HMM) framework reminiscent of Dynamic Time Warping from speech recognition. The state transitions enforce local velocity constraints and the most likely path sequence is recovered efficiently using the Viterbi algorithm. A rank reduction on the similarity probability matrix is used to provide additional robustness in challenging conditions when scoring sequence matches. We evaluate our approach on seven outdoor vision datasets and show improved precision-recall performance against the recently published seqSLAM algorithm.

Biometric identification method and system

Abstract: A biometric identification system ensuring reliable and protective identification of individuals even in a system having a biometric input device and a biometric verifier are separately provided is disclosed. The biometric data input device has a biometric data sensor and an encoder that encodes digital biometric data using secret information identifying the biometric data input device to transmit encoded data to the biometric verifier. The biometric verifier decodes the encoded data using the secret information to reproduce digital biometric data. The identity of the individual is verified when the digital biometric data is a registered biometric feature of an authorized user and the biometric data input device is an authorized device.

Handwritten sentence recognition

Abstract: We present a system for reading handwritten sentences and paragraphs The system's main components are preprocessing, feature extraction and recognition In contrast to other systems, whole lines of text are the basic units for the recognizer Thus the difficult problem of segmenting a line of text into individual words can be avoided Another novel feature of the system is the incorporation of a statistical language model into the recognizer Experiments on the database described previously by the authors (1999) have shown that a recognition rate on the word level of 795% and 6005% for small (776 words) and larger (7719 words) vocabularies can be reached These figures increase to 843% and 6732% if the top ten choices are taken into account

Robust Biometric Recognition From Palm Depth Images for Gloved Hands

Abstract: Biometric recognition can be used to improve gesture-based interfaces by automatically identifying operators. Traditional palm biometric recognition techniques depend on palm appearance features, but these features are not available in an operating theater where gloves are worn. We propose a depth-based solution for palm biometric recognition. Based on the depth image, our system automatically segments the user's palm and extracts finger dimensions. The finger dimensions are further scaled according to the sensed depth to obtain the true finger dimensions, which are then used as features to characterize the palm. Finally, a modified $k$ -nearest neighbors algorithm that assigns class labels based on the centroid displacement of each class in the neighboring points is applied to recognize the palm based on the geometric features. An accuracy of 96.24% was achieved for the biometric recognition of 4057 gloved palm samples captured at different angles and depths from 27 users. This accuracy is comparable with those of other state-of-the-art classification algorithms and demonstrates that biometric recognition may be viable for settings with gloved hands such as surgery.