Image Skew Correction Algorithm

This algorithm demonstrates exceptional performance in image skew correction and operates at higher speeds than competing algorithms. The implementation typically involves edge detection using operators like Sobel or Canny, followed by Hough transform to detect dominant lines and calculate skew angles. Key advantages include:

- High accuracy: The algorithm effectively corrects image skew through precise angle calculation, often achieving sub-degree precision using trigonometric transformations and interpolation techniques.

- Fast execution: Optimized computational methods allow rapid processing of large image datasets, with parallel processing capabilities for batch operations.

- Strong stability: Robust error handling maintains performance regardless of image complexity, incorporating noise reduction filters and adaptive thresholding.

- Excellent scalability: The code adapts to various image sizes and resolutions through dynamic parameter adjustment and multi-scale analysis approaches.

- High usability: Requires minimal parameter tuning and no specialized pre-processing, featuring automatic angle detection and correction functions.

In summary, this algorithm represents an outstanding solution for image skew correction, delivering superior performance in accuracy, speed, and stability that makes it highly suitable for practical applications.