Table Detection

Supervisor: Florian Kleber

Start: as soon as possible

Problem Statement

Document Image Analysis (DIA) deals with the analysis and recognition of document images. Tasks range from skew estimation, layout analysis to Handwritten Text Recognition (HTR). Tables in documents contain structured information which can allow a deeper insight into specific data. During layout analysis, one task deals with the detection of table regions within a document.

Goal

The goal of the practical course (Informatik Praktikum) / Bachelor thesis is to train a State of the Art Neural Network to detect table regions in document images. Datasets with annotated table regions (GT) are available.

Workflow
Literature research
Implementation in Python or C++
Evaluation of the system
Written report or bachelor thesis (in English) and final presentation

Requirements
Python or C++
Basic knowledge in Computer Vision
Basic knowledge in Deep Learning (Tensorflow, PyTorch) and Machine Learning