Character Skew Correction Implementation

In this program, we implement character skew correction to ensure text readability and accuracy. To achieve this, we employ computer vision techniques and machine learning algorithms. Specifically, we utilize image processing methods to detect irregular shapes and skew angles in text components through edge detection and Hough transform operations. The correction process involves calculating the skew angle using projection profile analysis and applying affine transformations to rotate the image. We leverage machine learning algorithms, particularly convolutional neural networks (CNNs), to recognize font characteristics and glyph patterns, enabling automated correction based on learned features. The implementation includes key functions such as pre-processing (grayscale conversion, noise reduction), skew angle detection, and image rotation using interpolation methods. Through these approaches, we provide users with an efficient, accurate, and user-friendly character skew correction program that handles various font types and text orientations.