Real-time thermographic image acquisition and segmentation algorithms for continuous material

This paper presents a real-time image acquisition and segmentation system. The system involves three main processes: acquisition, filtering and segmentation. Image acquisition is performed in the steel industry, where thermographic linear images are captured from strips (10 Km long and I meter wide) at a temperature between 100degreesC and 200degreesC while they are moving forward along a track. During the acquisition process a relationship between each pixel in the linear image and real-world units is established using a theoretical model whose parameters have been adjusted after a calibration process. After the acquisition, linear images are spatially filtered to reduce noise, and online with these processes (acquisition and filtering), segmentation is applied to the linear images to divide them into homogeneous temperature zones. Two different segmentation methods are evaluated: region merging and edge detection. To compare the segmentation algorithms an empiric segmentation evaluation method is defined. The segmentation evaluation method lies in comparing the results obtained from the algorithm with the theoretical segmentation defined by a group of experts. The evaluation method will determine the best segmentation algorithm, the optimal parameter and the effectiveness obtained using a test set.