An On‐Line Recognition System for Spoken Digits

1971 ◽  
Vol 49 (4B) ◽  
pp. 1288-1296 ◽  
Author(s):  
T. G. von Keller
Keyword(s):  
Recognition System ◽  
On Line

scholarly journals DOLARS, a Distributed On-Line Activity Recognition System by Means of Heterogeneous Sensors in Real-Life Deployments—A Case Study in the Smart Lab of The University of Almería

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 405
Author(s):  
Marcos Lupión ◽  
Javier Medina-Quero ◽  
Juan F. Sanjuan ◽  
Pilar M. Ortigosa
Keyword(s):  
Real Time ◽  
Activity Recognition ◽  
Real Life ◽  
Recognition System ◽  
Machine Learning Algorithms ◽  
Sensor Data ◽  
Heterogeneous Sensors ◽  
On Line ◽  
The University

Activity Recognition (AR) is an active research topic focused on detecting human actions and behaviours in smart environments. In this work, we present the on-line activity recognition platform DOLARS (Distributed On-line Activity Recognition System) where data from heterogeneous sensors are evaluated in real time, including binary, wearable and location sensors. Different descriptors and metrics from the heterogeneous sensor data are integrated in a common feature vector whose extraction is developed by a sliding window approach under real-time conditions. DOLARS provides a distributed architecture where: (i) stages for processing data in AR are deployed in distributed nodes, (ii) temporal cache modules compute metrics which aggregate sensor data for computing feature vectors in an efficient way; (iii) publish-subscribe models are integrated both to spread data from sensors and orchestrate the nodes (communication and replication) for computing AR and (iv) machine learning algorithms are used to classify and recognize the activities. A successful case study of daily activities recognition developed in the Smart Lab of The University of Almería (UAL) is presented in this paper. Results present an encouraging performance in recognition of sequences of activities and show the need for distributed architectures to achieve real time recognition.

A compliant control method for disassembly of non-elastic parts using realised motion

Robotica ◽  
1995 ◽  
Vol 13 (6) ◽  
pp. 591-598 ◽  
Author(s):  
Yagmur Denizhan
Keyword(s):  
Control Method ◽  
Recognition System ◽  
Automatic Recognition ◽  
Human Operator ◽  
Control Methods ◽  
Compliant Control ◽  
On Line

SummaryIn disassembly tasks, due to the large variety of objects and the different positions and orientations in which they appear, the disassembly trajectories supplied on-line by a human operator or an automatic recognition system can contain large errors. The classical compliant control methods turn out to be insufficient to eliminate sticking which is due to these errors. This paper presents a compliant control method for disassembly of non-elastic parts in non-elastic environments which adopts the trajectories according to realised motion. In case of sticking a new direction of motion is searched for until the manipulated part is set into motion.

A STRUCTURAL APPROACH TO ON-LINE CHARACTER RECOGNITION: SYSTEM DESIGN AND APPLICATIONS

1991 ◽  
Vol 05 (01n02) ◽  
pp. 311-335 ◽  
Author(s):  
FATHALLAH NOUBOUD ◽  
RÉJEAN PLAMONDON
Keyword(s):  
Character Recognition ◽  
Computation Time ◽  
Experimental Tests ◽  
Recognition System ◽  
Structural Approach ◽  
Chain Code ◽  
String Comparison ◽  
Average Computation Time ◽  
On Line ◽  
A Chain

This paper presents a real-time constraint-free handprinted character recognition system based on a structural approach. After the preprocessing operation, a chain code is extracted to represent the character. The classification is based on the use of a processor dedicated to string comparison. The average computation time to recognize a character is about 0.07 seconds. During the learning step, the user can define any set of characters or symbols to be recognized by the system. Thus there are no constraints on the handprinting. The experimental tests show a high degree of accuracy (96%) for writer-dependent applications. Comparisons with other system and methods are discussed. We also present a comparison between the processor used in this system and the Wagner and Fischer algorithm. Finally, we describe some applications of the system.

scholarly journals A Survey on the Classifiers in On-line Handwritten Uyghur Character Recognition System

2016 ◽  
Vol 9 (3) ◽  
pp. 189-198 ◽  
Author(s):  
Wujiahemaiti Simayi ◽  
Mayire Ibrayim ◽  
Dilmurat Tursun ◽  
Askar Hamdulla
Keyword(s):  
Character Recognition ◽  
Recognition System ◽  
On Line

Cancellable Biometrics for On-line Signature Recognition

2011 ◽  
pp. 290-315 ◽  
Author(s):  
Emanuele Maiorana ◽  
Patrizio Campisi ◽  
Alessandro Neri
Keyword(s):  
Recognition System ◽  
Design Of Algorithms ◽  
Biometric Data ◽  
The Public ◽  
Protection Scheme ◽  
Protection Method ◽  
Signature Database ◽  
On Line ◽  
Signature Recognition ◽  
Recognition Systems

With the widespread diffusion of biometrics-based recognition systems, there is an increasing awareness of the risks associated with the use of biometric data. Significant efforts are therefore being dedicated to the design of algorithms and architectures able to secure the biometric characteristics, and to guarantee the necessary privacy to their owners. In this work we discuss a protected on-line signature-based biometric recognition system, where the considered biometrics are secured by applying a set of non-invertible transformations, thus generating modified templates from which retrieving the original information is computationally as hard as random guessing it. The advantages of using a protection method based on non-invertible transforms are exploited by presenting three different strategies for the matching of the transformed templates, and by proposing a multi-biometrics approach based on score-level fusion to improve the performances of the considered system. The reported experimental results, evaluated on the public MCYT signature database, show that the achievable recognition rates are only slightly affected by the proposed protection scheme, which is able to guarantee the desired security and renewability for the considered biometrics.

A Robotic Facial Expression Recognition System Using Real-Time Vision System

2008 ◽  
Vol 381-382 ◽  
pp. 375-378
Author(s):  
K.T. Song ◽  
M.J. Han ◽  
F.Y. Chang ◽  
S.H. Chang
Keyword(s):  
Image Processing ◽  
Facial Expression ◽  
Real Time ◽  
Facial Expressions ◽  
Facial Expression Recognition ◽  
Vision System ◽  
Recognition System ◽  
Expression Recognition ◽  
On Line ◽  
Processing Platform

The capability of recognizing human facial expression plays an important role in advanced human-robot interaction development. Through recognizing facial expressions, a robot can interact with a user in a more natural and friendly manner. In this paper, we proposed a facial expression recognition system based on an embedded image processing platform to classify different facial expressions on-line in real time. A low-cost embedded vision system has been designed and realized for robotic applications using a CMOS image sensor and digital signal processor (DSP). The current design acquires thirty 640x480 image frames per second (30 fps). The proposed emotion recognition algorithm has been successfully implemented on the real-time vision system. Experimental results on a pet robot show that the robot can interact with a person in a responding manner. The developed image processing platform is effective for accelerating the recognition speed to 25 recognitions per second with an average on-line recognition rate of 74.4% for five facial expressions.

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