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@article{184557,
        author = {Pooja Kumari},
        title = {Design and Implementation of Edge Detection Algorithm For Image Processing},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {4},
        pages = {1833-1840},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=184557},
        abstract = {Digital image processing have become the mostly explored areas of modern technology due to its vast applications in medical imaging, surveillance, robotics, and computer vision. Traditionally, in many of the image edge detector algorithms are executed using techniques like computer simulation, which make testing and validation relatively simple. However, when algorithms or architectures grow in complexity, increases the time of simulation drastically. This makes the computational cost high and also makes software-based implementations unsuitable for real-time, high-speed image and video applications. To overcome this limitations, hardware-based solutions, particularly FPGA architectures, are adopted because of parallel processing capability, it is reconfigurable, and reduced latency. This work presents an FPGA-based realization of the Canny edge detection algorithm, incorporating adaptive thresholding to improve the performance of image processing applications. Unlike fixed thresholds, adaptive thresholding dynamically adjusts to varying illumination and noise conditions, thereby improving edge localization accuracy and robustness. The proposed architecture integrates Gaussian smoothing, gradient computation, non-maximum suppression, and adaptive thresholding, followed by edge tracking. The complete design is modeled and programmed in Verilog, simulated and synthesized using Xilinx Vivado tools. Experimental results demonstrate that the modified design reduces memory requirements and latency while maintaining high throughput and strong edge detection performance, outperforming conventional fixed-threshold Canny implementations.},
        keywords = {Image Processing, HDL, MATLAB, Thresholding.},
        month = {September},
        }