This research investigates the impact of graphical representation on the accuracy of three-dimensional shape classification. 3D models, both canned and modeled, are used in engineering, computer graphics and scientific data visualization. Various approaches are adopted in these fields to visually epresent 3D geometry, utilizing solutions such as OpenGL and Direct3D, each with its distinct goal of achieving either real-time manipulation or photorealism. the purpose of this research was to determine the most effective graphical representation for categorizing mechanical components with a high degree of geometric similarity, such as beams and rods. The study examined various image representations and their combinations, obtained through the adjustment of rendering parameters and image compositing. In an effort to improve classification accuracy, novel techniques for addressing image recognition issues were developed and tested against commonly used image representation methods. This innovative approach proposed in the paper led to a 48% reduction in classification errors.