The interest for the use of photoelasticity in experimental applications of the determination of stress, and its use in industry as a quality control and inspection tool hás been stimulated thanks to the micro computing evolution, the equipment and software able to capture and process images. Currently, new video boards, motherboards and increased CPU processing speed have made significant progress in white light photoelasticity automation. The present work describes, initially, the recent progress of the automatic photoelasticity fringe orders (N) determination, by means of monochromatic light use (Gray Photoelasticity) until the current state of art, in which white light is used, called Three Color Photoelasticity (or RGB Photoelasticity (1)). Topics about photoelastic models, image acquisition and RGB capture, including programming instructions, are addressed, as well as procedures for obtaining appropriate images. Additionally, innovations using master tables for comparison are presented to improve the determination of N by conventional methods. Two methods, based on specially developed algorithms, are proposed to improve the quality of N determination. In the first method wrong estimates are identified and substituted through linear interpolation among neighboring points. In the second method, fuzzy logic fundamentals are used to re-define the estimates. The main purpose of this work is to prove the viability of a new line of research, where its objective is to obtain, through a single photoelastic model image, extremely accurate N values. Through this research, valuable tools can be derived from the application of artificial intelligence techniques, specifically the fundamentals of fuzzy logic. (Kt) and Stress Intensity Factor (Kl) from the fringe order values (N) obtained from RGB Photoelastic models is readily apparent and has a clear advance over the methods. The main results of this work were implemented in a computer program and some examples were presented. The possibility to obtain the Stress Concentration Factor Other example is the practical application in the glass industry, where the undesirable tractive residual stress detection is greatly improved.