From the last ancient the significance of biometrics has been truly configured due to its important in the every day lifestyles that begins from civilian functions to military actions as well as commercial applications. A Footprint cognizance is a one type of the excellent personal identity based totally on biometric measures. The intention of this research is to sketch a desirable and reliable left foot tip biometric system entitled (LFBS). This paper provides a robust varied technique which connects between two important technology techniques they are Image Processing and Artificial Intelligent technique via Bird Swarm Optimization Algorithm (BSA) to apprehend the human footprint. The use of (BSA) enhances the overall performance and the quality of the outcomes produced from the proposed biometric application via function selection. The chosen facets were once handled as the top of the line attribute set in places of characteristic collection size. The visual database was once developed through capturing life RGB footprint images . Freeman chain code was used with footprint template (black and white image), then statistical values which represent the footprint features was extracted. These aspects have been extracted from every image and saved in Excel file to be entered into the Bird Swarm Algorithm. The experimental effects exhibit that our algorithm estimates, terrific consequences with a tiny feature set in evaluation with different algorithms. On the other hand experimental about 100% accuracy in relation with different papers on the same field. Results show that our algorithm achieves well-organized and precise result.