Applying fuzzy theory in selecting the image quality factors of 3D televisions

Abstract

With the promotion of technology, state-of-the-art TVs already possess the functions of 3D. This study applied fuzzy theory to construct a hierarchy of 3D TV image quality factors and got the weights for each of them. Several 3D TV image quality factors were selected based on a review of the literature. A fuzzy c-means algorithm was then used to classify these factors into the criteria, and the hierarchy of the fuzzy analytic network process (ANP) was established. Thirty participants were recruited to conduct the questionnaire survey and the rating of the overall ergonomics. Using the calculation of fuzzy ANP, the weights for 3D TV image quality factors and different brands of 3D TVs were obtained. The results indicated that binocular disparity, crosstalk, and resolution were the three most important factors affecting 3D TV image quality. Therefore, 3D TV manufacturers could consider these important factors in future 3D TV product designs in order to promote customers’ purchase intention. Relevance to industryBased on the results obtained from fuzzy ANP, this study found that the three most important factors affecting 3D TV image quality are binocular disparity, crosstalk, and resolution. The results of this study could serve as a reference for 3D TV manufacturers in designing future products.