Browsing by Author "Kaur, Balvinder"
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Item An Approach to Detect Human Facial Skin in Thermal Imagery(2012-09-17) Kaur, Balvinder; Kaur, Balvinder; Nelson, Jill K.Image processing tools to detect human skin in visible band imagery have been well explored by many organizations, and approaches have been developed for many security and military applications. Visible cameras are limited to human skin detection during daylight or artificial illumination conditions, but the challenge of human skin detection during nighttime remains an ongoing research effort. The most challenging problems are to understand skin texture and to develop mathematical tools for discriminating skin texture from non-skin textures in images collected using a single thermal band. To solve this problem, a set of image processing algorithms have been designed and developed for generating the skin-texture feature set discriminating feature selection, and classification. First, Gray Level Co-occurrence Matrix (GLCM)-driven skin-texture features are generated based on the skin portions of the imagery. Principal Component Analysis (PCA) is then performed on the feature set to isolate the skin discriminating features. Then, PCA-reported skin discriminating features are employed to construct a fused image. The purpose of this fused image is to represent the skin pixels in terms of the skin-discriminating features and use this image for skin discrimination. In the last process, this fused image is used for skin and non-skin classification at the local level. For classification, three image processing approaches are adopted: 1) Adaptive optimized threshold with Least Mean Square algorithm, 2) Principal Component Analysis (PCA), and 3) Linear Discriminant Analysis (LDA). Results from all three classification techniques are analyzed for accuracy confidence levels. This research provides a generalized approach for human skin detection in thermal images, providing a noncontact, remote, and passive method for human skin detection in day or night imagery for security and military applications.Item Visible Spectrum Based Non-Contact Detection and Characterization of Blood Wave Signal Dynamics and Applications in Stress Detection(2016) Kaur, Balvinder; Kaur, Balvinder; Ikonomidou, Vasiliki NStress is a major health concern that not only compromises our quality of life, but also affects our health and well-being. Despite its importance, our ability to objectively detect and quantify stress in a real-time, non-invasive manner is limited. This capability would have a wide variety of medical, military, and security applications. Under the dissertation research, we have developed a pipeline of image and signal processing algorithms for such a capability, which includes remote blood wave (BW) signal detection based on minor color intensity fluctuations in visible spectrum videos of the human skin during the cardiac cycle, and physiological stress measurements based on the temporal variability in these remotely detected cardiac signals.