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$GTCH developing real time algorithms and techniques for Kirlian research. A Kirilian image includes vast amount of graphical data. GBT/Tokenize research is aiming to develop a system and method to analyze this data as a potential of health-related information source. These algorithms and methods are pattern detection and recognition, based on unique principles. An image’s objects are categorized according to their physical characteristics like shape, color, texture, and more. A machine learning based flow is targeted to operate as an object’s classifier and analytics processor. We believe that the object detection and analytics method can be used for processing Kirlian images for their characteristics as another stage of GBT/Tokenize’s Kirlian Electrophotography research. Kirlian photography method introduces a series of techniques that are based on the phenomenon known as electrical coronal discharge.