In this project, we've leveraged image processing techniques to efficiently analyze cell images, ensuring both aesthetic quality and accurate counting. Our focus has been on identifying various types of red blood cells (RBCs) in human samples. By employing sophisticated mathematical formulas, we've optimized the process for precise identification and counting, thereby enhancing our understanding of cellular composition and aiding in medical diagnostics
