Thermal Image-Based Object Classification for Guiding the Visually Impaired. (4th August 2020) - Nancy, V; Balakrishnan, G
Abstract: Thermal sensors are now being an emerging technology in image processing applications such as face recognition, fault detection, object detection and classification, navigation, etc. Owing to its versatility, it has been an influential concern for many researchers recently. Thermal sensors have proficiency of sensing the object heedless of the lighting conditions. Due to this added leverage of thermal sensors, we propose a novel scheme for spotting the object, which is targeted by a specific thermal camera. The accomplishment of this task paves the opportunity for guiding the visually impaired (VI) people within the indoor environment adequately. Augmenting the obstacles in the user's path is requisite for the VI people's navigation. The image of the object is captured using the thermal camera and pre-processed for enhancing the quality of that image by suppressing the background, tuning the colour channels, etc. Noise in the thermal image is eradicated to a certain extent using Gaussian smoothing process followed by Markov random field for constructing the Gaussian mixture model. Further, the pattern is deduced and classified based on the least-squares support-vector machine. The experiment is tested for disparate timing and distance, and the optimum solution is obtained. To enact the accurate outcome with short estimation period in affordable size and cost is the main added logic behind this fused concept .