This paper presents a generic method to process mid-wave infrared (MWIR) images in laserbased manufacturing processes. The background noise of the camera is used as a source of information for correcting different problems that affect MWIR cameras. The mean of the noise distribution is used to correct the background drift due to sensor heat-up, whereas the standard deviation is used to generate dynamic thresholds for subsequent algorithms. The proposed method is portable, robust, and independent of the background, scale, and optical and electronic aberrations of the camera. The method is validated in the calculation of melt pool cooling rate. Performance is tested in a real scenario using a Field Programmable System-on-Chip platform. Results show that the system is capable of sending to a remote computer MWIR images at 1,435 frames per second and cooling rate information at a rate of 10,680 samples per second.

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