Custom Edge Detection Algorithm

I have designed a custom edge detection method that accurately extracts image edges with straightforward implementation. This algorithm employs gradient calculation using convolution kernels (such as Sobel or Prewitt operators) combined with adaptive thresholding to precisely locate object boundaries. The method allows easy extraction of boundary information from various objects within images, facilitating subsequent image analysis and processing tasks. Through careful parameter optimization and noise handling mechanisms, this approach maintains high efficiency while preserving accuracy even when processing complex images. The implementation typically involves key steps: image preprocessing (noise reduction), gradient magnitude computation, non-maximum suppression, and hysteresis thresholding. This custom edge detection method demonstrates significant application potential and can contribute innovative solutions to the field of image processing and computer vision.