Breakages of both warp and weft yarns are one of the most prevalent issues in textile technology today. This issue lowers the quality of the fabric produced as well as the production pace. Numerous forms of fabric flaws still need to be found by hand examination in the case of contemporary weaving techniques. The purpose of this work is to present an efficient and precise technique for automatically identifying fabric defects. Using Aphelion Dev software, statistical characteristics including mean, standard deviation, kurtosis, skewness, and histogram representation of fabric photographs are taken into consideration when comparing fabrics with and without faults. To provide a precise result for fabric flaws, morphological approaches are applied. The finished image has been integrated into an open platform for multimedia applications, speeding up processing time by 60ns. This method excels at finding fabric flaws with greater accuracy, effectiveness, and in less time.