Real time railway extraction by angle alignment measure

Rail extraction is a fundamental and important step in railway Driver Assistant System, which is now an important application of image processing. The task is challenging as the railway is exposed to different environments. This paper proposes a railway extraction scheme, using a novel connectivity measure method named Angle Alignment Measure. The proposed scheme is robust to luminance and color variation, without edge extraction process. Railways with different lengths and patterns can be extracted under various lighting and weather conditions. More importantly, the computation complexity of the proposed scheme is very low, requiring only on average 25ms to process a frame on smart phone and 5ms on desktop computer, which are significantly better than algorithms in the literature.

[1]  Thambipillai Srikanthan,et al.  Robust extraction of lane markings using gradient angle histograms and directional signed edges , 2012, 2012 IEEE Intelligent Vehicles Symposium.

[2]  Ralph Ross,et al.  Vision-based track estimation and turnout detection using recursive estimation , 2010, 13th International IEEE Conference on Intelligent Transportation Systems.

[3]  Monson H. Hayes,et al.  A Novel Lane Detection System With Efficient Ground Truth Generation , 2012, IEEE Transactions on Intelligent Transportation Systems.

[4]  In So Kweon,et al.  Finding and tracking road lanes using "line-snakes" , 1996, Proceedings of Conference on Intelligent Vehicles.

[5]  Luis Salgado,et al.  Log-Gabor Filters for Image-Based Vehicle Verification , 2013, IEEE Transactions on Image Processing.

[6]  Thambipillai Srikanthan,et al.  Gradient angle histograms for efficient linear hough transform , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[7]  Bogdan Stanciulescu,et al.  Rail extraction technique using gradient information and a priori shape model , 2012, 2012 15th International IEEE Conference on Intelligent Transportation Systems.

[8]  Zehang Sun,et al.  Monocular precrash vehicle detection: features and classifiers , 2006, IEEE Transactions on Image Processing.

[9]  Bogdan Tomoyuki Nassu,et al.  A Vision-Based Approach for Rail Extraction and its Application in a Camera Pan–Tilt Control System , 2012, IEEE Transactions on Intelligent Transportation Systems.

[10]  Wan-Chi Siu,et al.  Real time moving object detection using motor signal and depth map for robot car , 2013, Electronic Imaging.

[11]  ZuWhan Kim,et al.  Robust Lane Detection and Tracking in Challenging Scenarios , 2008, IEEE Transactions on Intelligent Transportation Systems.

[12]  Chung Sheng-Luen,et al.  Android-based driving assistant for lane detection and departure warning , 2014, Proceedings of the 33rd Chinese Control Conference.

[13]  Kwanghoon Sohn,et al.  Gradient-Enhancing Conversion for Illumination-Robust Lane Detection , 2013, IEEE Transactions on Intelligent Transportation Systems.

[14]  Monson H. Hayes,et al.  Robust lane detection and tracking with ransac and Kalman filter , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[15]  Wen-Hsiang Tsai,et al.  Hough transform with dynamic thresholding for robust and real-time detection of complex curves in images , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[16]  Jürgen Wohlfeil,et al.  Vision based rail track and switch recognition for self-localization of trains in a rail network , 2011, 2011 IEEE Intelligent Vehicles Symposium (IV).

[17]  Ronen Lerner,et al.  Recent progress in road and lane detection: a survey , 2012, Machine Vision and Applications.

[18]  Wan-Chi Siu,et al.  Accurate distance estimation using camera orientation compensation technique for vehicle driver assistance system , 2012, 2012 IEEE International Conference on Consumer Electronics (ICCE).

[19]  Francesca Odone,et al.  Histogram intersection kernel for image classification , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[20]  Yusuf Sinan Akgul,et al.  Vision-based railroad track extraction using dynamic programming , 2009, 2009 12th International IEEE Conference on Intelligent Transportation Systems.