Line Segmentation

Line segmentation, the process of dividing a document image into individual text lines, is crucial for accurate optical character recognition (OCR) and document analysis. Current research focuses on improving segmentation accuracy and robustness, particularly for challenging scenarios like handwritten text, historical documents with degraded quality, and images with complex layouts, employing techniques such as convolutional neural networks (CNNs), object detection models (e.g., YOLO), and attention mechanisms to address variations in writing styles and image characteristics. These advancements are vital for improving the efficiency and accuracy of automated document processing in diverse applications, ranging from digitizing historical archives to automating power line inspection from aerial imagery.