The color shade of dyed fabric or printed fabric color defect plays a major role in determining the quality of fabric color. Hence there is a need for inspection of color shade for its quality. Conventionally inspection for quality of color and defect in color shade is carried out either manually in mainstream of industries or by using color matching cabinet technique. In this paper, the focus is on the inspection of the variations in color strength and color shade of single uniform color using various LAB space models on computer generated image samples without any manual help for clarification. RGB colors sensor process is used various fields for analyzing different applications such as medical sciences, biological sciences. Various color sensor image types have been used to detect shade variation. This work is analyzed and compared two types of color sensor original frequency RGB and current frequency RGB color space, RGB color sensor and the comparative result is given. Methods/Statistical Analysis: We examined and analyzed the RGB original value and RGB detected current value sensor with color space using techniques such as pre-processing, segmentation, clustering for detecting shade of color, Results/Finding: In detecting the solid color, color becomes an important feature to identify the shade variation color and matching. We have considered RGB color sensor and used for garment enhancement and segmentation for extraction of the variation garment sample which are used to identify the shade mismatch level. Conclusion: RGB color sensor has given better clarity and RGB detection value which is suitable for fabric shade detection than computer color matching and color match cabinet