Interpretation of Human Energy Fields Using Advanced Image Processing Techniques

Wong, Li Qian (2025) Interpretation of Human Energy Fields Using Advanced Image Processing Techniques. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

This project investigates the use of advanced image processing techniques to interpret human energy fields, which are believed to reflect an individual’s mental, emotional, and physical states. Building upon previouswork, this study focuses on developing a post-processing tool that quantifies changes in the visual characteristics of human energy field images before and after energy-based therapies. Key parameters analyzed include brightness, texture, and symmetry. Brightness is measured using the HSV color model, while texture is evaluated through GLCM texture features. Symmetry is assessed using an improved axis detection and Structural Similarity Index (SSIM) method. The developed algorithm was validated across multiple participants, demonstrating consistent and reliable detection of visual changes. Results are presented in tabulated form for straightforward comparison. The tool’s sensitivity to subtle variations and its repeatability strengthen its potential application in energy field research, offering a standardized approach to analyze changes without relying solely on subjective interpretation. The developed algorithm was validated on 22 participants, quantifying brightness (0–100%), GLCM texture features, and symmetry (0.00–1.00 via SSIM).