Focusing in thermal imagery using morphological gradient operator

• We presents focusing on an object of interest in a thermal infrared (IR) image.
• Thermal IR images do not have strong edge components of an object.
• Focusing on an object must retain prominent features of the object for recognition.
• Morphological gradient operator outperforms conventional gradient operators.

This paper presents focusing on an object of interest in thermal infrared (IR) imagery using the morphological gradient operator. Most existing focus metrics measure the degree of sharpness on the edge of an object in the field of view, often based on the local gradient operators of pixel brightness intensity. However, such focus measures may fail to find the optimal focusing distance to the object in thermal IR images, where strong edge components of an object do not exist. In particular, when the end goal of image acquisition is object recognition, focusing on an object must retain prominent features of the object for recognition. In this paper, the performances of various focus measures are evaluated in terms of sharpness as well as recognition accuracies for face recognition in thermal IR images. Experiment results show that the morphological gradient operator outperforms conventional gradient operators in terms of autofocusing resolution metric as well as face recognition accuracy.