Extraction of blood vessels from retinal images is crucial for diagnosing various retinopathy diseases, including diabetic retinopathy, hemorrhage, macular degeneration, and retinal injuries. Accurate vessel extraction enables early detection and monitoring of these conditions, significantly impacting patient outcomes. This paper presents a novel technique for precise blood vessel extraction in retinal images, using an amalgamation of advanced image enhancement techniques. The method begins with background normalization using a large kernel mean filter to detect vessel lines. Top Hat Transformation is then applied to enhance these lines, followed by a vessel filling technique to improve their visibility. Finally, a boundary omission technique is used to remove the retinal border from the image. The resultant image showcases enhanced accuracy and clearer depiction of the extracted blood vessels, facilitating better analysis and diagnosis.