Graphical Object Detection in Document Images

08/25/2020
by   Ranajit Saha, et al.
0

Graphical elements: particularly tables and figures contain a visual summary of the most valuable information contained in a document. Therefore, localization of such graphical objects in the document images is the initial step to understand the content of such graphical objects or document images. In this paper, we present a novel end-to-end trainable deep learning based framework to localize graphical objects in the document images called as Graphical Object Detection (GOD). Our framework is data-driven and does not require any heuristics or meta-data to locate graphical objects in the document images. The GOD explores the concept of transfer learning and domain adaptation to handle scarcity of labeled training images for graphical object detection task in the document images. Performance analysis carried out on the various public benchmark data sets: ICDAR-2013, ICDAR-POD2017,and UNLV shows that our model yields promising results as compared to state-of-the-art techniques.

READ FULL TEXT

page 3

page 5

research
06/23/2023

Bridging the Performance Gap between DETR and R-CNN for Graphical Object Detection in Document Images

This paper takes an important step in bridging the performance gap betwe...
research
04/17/2018

A Saliency-based Convolutional Neural Network for Table and Chart Detection in Digitized Documents

Deep Convolutional Neural Networks (DCNNs) have recently been applied su...
research
11/30/2017

Multi-Channel CNN-based Object Detection for Enhanced Situation Awareness

Object Detection is critical for automatic military operations. However,...
research
10/28/2019

Fine-Grained Object Detection over Scientific Document Images with Region Embeddings

We study the problem of object detection over scanned images of scientif...
research
01/08/2020

Techniques d'anonymisation tabulaire : concepts et mise en oeuvre

In this document, we present a state of the art of anonymization techniq...
research
06/01/2020

Symbol Spotting on Digital Architectural Floor Plans Using a Deep Learning-based Framework

This papers focuses on symbol spotting on real-world digital architectur...
research
11/17/2016

Learning to detect and localize many objects from few examples

The current trend in object detection and localization is to learn predi...

Please sign up or login with your details

Forgot password? Click here to reset