Boundary recognition plays a vital role in real-world scenarios like medical imaging and surveillance. The classical edge detector fails to preserve minute details in the image. The abdominal CT images were first analyzed using two edge detection techniques based on gauss gradient are proposed here for real-time data processing. The performance of the edge detectors is validated by performance metrics and verified for benchmark dataset images. The results reveal that the gauss gradient edge detector was efficient for the boundary extraction in benchmark and medical images. The VLSI implementation of the proposed gauss gradient edge detectors is done using the Kintex 7-FPGA board, hardware implementation also generates efficient results with reduced execution time.