March 17, 2017

Combining convolutional neural networks and Hough Transform for classification of images containing lines

Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 103411C (17 March 2017); doi: 10.1117/12.2268717

In this paper, we propose an expansion of convolutional neural network (CNN) input features based on Hough Transform. We perform morphological contrasting of source image followed by Hough Transform, and then use it as input for some convolutional filters. Thus, CNNs computational complexity and the number of units are not affected. Morphological contrasting and Hough Transform are the only additional computational expenses of introduced CNN input features expansion. Proposed approach was demonstrated on the example of CNN with very simple structure. We considered two image recognition problems, that were object classification on CIFAR-10 and printed character recognition on private dataset with symbols taken from Russian passports. Our approach allowed to reach noticeable accuracy improvement without taking much computational effort, which can be extremely important in industrial recognition systems or difficult problems utilising CNNs, like pressure ridge analysis and classification.

Test Drive Our Smart Engines

Free demo apps allow you to experience the power of Smart Engines software for intelligent document scanning in a real-world context.

Why not experience the power of Smart Engines for yourself? Our demo apps allow you to test the capabilities of our identity document recognition software on mobile devices in videostream or in a single image (photo, scan).

Simply display any document to the camera in real-time or choose a photo from the gallery, and the app will recognize and capture the necessary data.

Demo apps Privacy Policy

id documents enginge by Smart Engines
Apple App Store Badge
Google Play Badge
id documents enginge by Smart Engines

Get in Touch

For questions about our products, research, people or project proposals, please get in touch.

Contact Form
Warning before submitting your request:

Smart Engines is fully committed to provide an answer within 2 working days. However, it is your responsibility that your IT infrastructure does not block our reply or redirect it into your spams. If you haven’t received any answer from us within 2 working days, please check your spams or simply call us.

Smart Engines guarantees that the provided information will not be made public and will be used only internally.