Dahua Ranked First in Two Challenges of ICDAR Competition

Times:2017-10-18 Browse:1891

HANGZHOU, China /October 18, 2017 As is shown on ICDAR Robust Reading 2015 official website, on October 17th, 2017, Dahua Technology took the 1st place in Task [Word Recognition] of Incidental Scene Text Challenge and Born-Digital Image Challenge–with an accuracy of 82.76% and 97.43% respectively.


The Result of Task [Word Recognition] in Incidental Scene Text Challenge

The Result of Task [Word Recognition] in Born-Digital Image Challenge


The International Conference on Document Analysis and Recognition (ICDAR) is an international academic conference which is held every two years in a different city. The ICDAR Robust Reading Competition has been held five times in 2003, 2005, 2011, 2013 and 2015. The competition is organized around challenges that represent specific application domains for robust reading.

Incidental Scene Text, a new challenge to the 2015 edition of the competition, is the most difficult one. It refers to text that appears in the scene without the user having taken any specific prior action to cause its appearance or improve its positioning /quality in the frame. Incidental scene has strong relevance to a wide range of applications linked to wearable cameras or massive urban captures where the capture is difficult to control.

A Fine Example of Incidental Scene Text


Born-Digital Image is one of the two challenges that start from the very first edition of the competition - ICDAR 2011. It refers to images saved by digital devices from the Internet and emails. Automatically extracting text from born-digital images is an interesting prospect as it would provide the enabling technology for a number of applications such as improved indexing and retrieval of Web content, enhanced content accessibility, content filtering (e.g. advertisements or spam emails) etc.

Robust Reading &ICDAR 2015

"Robust Reading" refers to the research area dealing with the interpretation of written communication in unconstrained settings. It has significant implication to video surveillance applications such as vehicle license plate recognition (LPR), container serial number recognition, logistics label context recognition and the recognition of text captured in normal surveillance.

Dahua OCR

Dahua AI OCR team from Dahua Advanced Research Institute participated in the ICDAR Robust Reading 2015 competition. Based upon deep learning technology and the advantages of SENet and ResNet network structure, Dahua team developed a unique strategy of multi-featured and multi-channel integration. Deployed together with multi-model integration technology, it greatly enhanced the accuracy of result.

The technologies utilized in this competition have been widely applied in Dahua smart transportation solutions. Breakthrough performance was achieved in situations dealing with tilted car plate, with recognition rate reaching up to 99.99%.


Examples of Car License Plate Recognition and Container Serial Number Recognition

In recent years, deep-learning has led to revolutionary breakthroughs to Intelligent Video Analytics. The accuracy of recognition is better than human being in many situations. It becomes possible and economically viable to automate many tasks not possible before. AI has been widely applied in public security, transportation and banking to protect property and people. With a mission of “Enabling a safer society and smarter living”, Dahua will continue to focus on “Innovation, Quality, and Service” to serve partners and customers around the world.