Fast Pattern Recognition Method for Eddy Current Testing

One of the benefits of eddy current (EC) testing is the attainability of high testing speeds while maintaining high sensitivity and requiring little with regard to material preparation. For this reason it is commonly automated and integrated in production lines of semi-finished products such as bars, tubes and wires. Because of the requirements of high throughput on-line digital analysis of EC signals is rarely applied, in contrast to ultrasonic testing. However, the usual methods of analog filtering and phase-selective or phase-insensitive threshold evaluation of EC signals are limited in regard to the suppression of false or pseudo-defect indications, classification of defect types, quantitative assessment of defect features and the suppression of signals originating from manmade structures

Fire – flexible image retrieval engine: Imageclef 2004 evaluation

Abstract. We describe FIRE, a content-based image retrieval system, and the methods we used within this system in the ImageCLEF 2004 evaluation. In FIRE, various features are available to represent images. The diversity of available features allows the user to adapt the system to the task at hand. A weighted combination of features admits flexible query formulations and helps with processing specific queries. For the ImageCLEF 2004 evaluation, we used the image content alone and obtained the best result in the category “only visual features, fully automatic retrieval ” in the medical retrieval task. Additionally, the results compare favorably to other systems, even if they make use of the textual information in addition to the images.