In this study the potential usefulness of infrared thermography (IRT) as a non-invasive tool to rapidly screen the most common non-infectious foot lesions in dairy cows was evaluated. Thirty-eight healthy cows and 38 cows affected by foot diseases were enrolled. Diseased cows showed the following disorders at lateral and medial claw in the hind foot: white line lesion, sole ulcer, sole haemorrhage, horizontal fissure, axial fissure. Thermography images of hind foot were collected for each animal using a digital infrared camera. Foot temperature was measured in four regions: central area of the hind foot (A1), interdigital area of the hind foot (A2), lateral (A3) and medial (A4) claw in the hind foot. Higher temperature values in the regions A1 and A2 compared to A3 and A4 were found in both healthy and diseased cows (p<0.001). Cows affected by foot diseases showed higher foot temperature values compared to healthy cows (p<0.05) in all considered regions. This study highlights the potential application of IRT as a reliable, practical tool for detection of hoof lesions in dairy cows. Multiple scanning images and comparisons between affected and healthy anatomical structures could be useful in defining the consistency of abnormality.
Development of facial recognition or expression recognition algorithms requires input data to thoroughly test the performance of algorithms in various conditions. Researchers are developing various methods to face challenges like illumination, pose and expression changes, as well as facial disguises. In this paper, we propose and establish a dataset of thermal facial images, which contains a set of neutral images in various poses as well as a set of facial images with different posed expressions collected with a thermal infrared camera. Since the properties of face in the thermal domain strongly depend on time, in order to show the impact of aging, collection of the dataset has been repeated and a corresponding set of data is provided. The paper describes the measurement methodology and database structure. We present baseline results of processing using state-of-the-art facial descriptors combined with distance metrics for thermal face reidentification. Three selected local descriptors, a histogram of oriented gradients, local binary patterns and local derivative patterns are used for elementary assessment of the database. The dataset offers a wide range of capabilities – from thermal face recognition to thermal expression recognition.