Table Image Understanding

Interactive Learning of a Multiple-Attribute Hash Table Classifier for Fast Object Recognition

Recovering ball motion from a single motion-blurred image

Motion blur often affects the ball image in photographs and video frames in many sports such as tennis, table tennis, squash and golf. In this work we operate on a single calibrated image depicting a moving ball over a known background, and show that motion blurred ball images, usually unwelcome in computer vision, bear more information than a sharp image. We provide techniques for extracting s...

Table Structure Identification from Document Images: A Survey

Table structure identification has received significant research attention in the past few years. The OCR (Optical Character Recognition) has faced many potential errors in the document images, so it is strongly required to make logical objects such as table explicit. So to get the deep understanding about the contents of the document, proper understanding of the document is required by means o...

Layout and Language: Challenges for Table Understanding on the Web

In this paper, we consider the table understanding task and present a catalogue of particular issues that arise when the tables are those found on the web. In addition, we consider what happens when processes commonly associated with web pages are applied to those bearing tables. 1 Table Understanding and the Web The ubiquity of tables, and their ability to describe relational information in a ...

Linear-time connected-component labeling based on sequential local operations

This paper presents a fast algorithm for labeling connected components in binary images based on sequential local operations. A one-dimensional table, which memorizes label equivalences, is used for uniting equivalent labels successively during the operations in forward and backward raster directions. The proposed algorithm has a desirable characteristic: the execution time is directly proporti...