Statistical methods for speech recognition
Statistical methods for speech recognition
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Direct Gray-Scale Extraction of Features for Character Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A High Accuracy Rate Commercial Flight Coupon Recognition System
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Multilingual Speech Processing
Multilingual Speech Processing
IEEE Transactions on Computers
Extraction and Recognition Alphabetic and Digital Characters on Industrial Containers
CIS '09 Proceedings of the 2009 International Conference on Computational Intelligence and Security - Volume 01
Automatic Numeric Characters Recognition of Kilowatt-Hour Meter
SITIS '09 Proceedings of the 2009 Fifth International Conference on Signal Image Technology and Internet Based Systems
A cognitive and video-based approach for multinational License Plate Recognition
Machine Vision and Applications
An automated vision system for container-code recognition
Expert Systems with Applications: An International Journal
A License Plate-Recognition Algorithm for Intelligent Transportation System Applications
IEEE Transactions on Intelligent Transportation Systems
License Plate Recognition From Still Images and Video Sequences: A Survey
IEEE Transactions on Intelligent Transportation Systems
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
An Algorithm for License Plate Recognition Applied to Intelligent Transportation System
IEEE Transactions on Intelligent Transportation Systems
| Hi-index | 12.05 |
In industrial applications optical character recognition with smart cameras becomes more and more popular. Since these applications mostly have challenging environments for the systems it is most important to have very reliable character segmentation and classification algorithms. The investigations of several algorithms have shown that character segmentation is one if not the main bottleneck of character recognition. Furthermore, the requirements of robust and fast algorithms related to skew angle estimation and line segmentation, as well as tilt angle estimation, and character segmentation are high. This is the reason for introducing such algorithms that are specifically adapted to industrial applications. Additionally, a method is proposed that is based on the Bayes theorem to take account of prior knowledge for line and character segmentation. The main focus of the investigations of the character recognition system is recognition performance and speed, since real-time constraints are very hard in industrial application. Both requirements are evaluated on an image series captured with a smart camera in an industrial application.