Document Image Processing

Module: Computer Vision | Difficulty: Intermediate

Document Layout Analysis

Layout Detection

Detect regions: text, table, figure, title, list.

Table Structure Recognition

Reading Order Detection

DocVQA

import torch
import torch.nn as nn

class LayoutDetector(nn.Module):
    def __init__(self, num_classes=5):
        super().__init__()
        self.backbone = nn.Sequential(
            nn.Conv2d(3, 64, 3, padding=1), nn.ReLU(True),
            nn.AdaptiveAvgPool2d((7, 7)),
        )
        self.box_head = nn.Linear(64 * 7 * 7, 4)
        self.cls_head = nn.Linear(64 * 7 * 7, num_classes)
    
    def forward(self, x):
        feat = self.backbone(x).flatten(1)
        return self.box_head(feat), self.cls_head(feat)

Key Takeaways

• Document understanding requires layout, text, and structure analysis
• Table recognition involves both detection and structure parsing
• Modern approaches use end-to-end transformer models