Road crack detection using color variance distribution and discriminant analysis for approaching smooth vehicle movement
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ORIGINAL ARTICLE
Road crack detection using color variance distribution and discriminant analysis for approaching smooth vehicle movement on non-smooth roads Chinthaka Premachandra • H. Waruna H. Premachandra Chandana Dinesh Parape • Hiroharu Kawanaka
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Received: 23 December 2013 / Accepted: 12 February 2014 Ó Springer-Verlag Berlin Heidelberg 2014
Abstract We present an image analysis based automatic road crack detection method for conducting smooth driving on non-smooth road surfaces. In the new proposal, first the road surface areas which include cracks are extracted as crack images by analyzing the color variance on norm. Then cracks are extracted from those areas by introducing a method on discriminant analysis. According to experiments using the images of different road surfaces, the new proposal showed better performances than the conventional approaches. Keywords Smooth driving Cracks Image sample variance Discriminant analysis
1 Introduction Vehicle technology has been invented several decades ago and extremely fast development has been achieved. Car industries and some Universities in the world have developed vehicles focusing different directions such as environment friendly vehicles and easy drivable vehicles. For C. Premachandra (&) Tokyo University of Science, 6-3-1 Niijuku, Katsushikaku, Tokyo 125-8585, Japan e-mail: [email protected] H. W. H. Premachandra Wayamba University of Srilanka, Makadura, Srilanka C. D. Parape Kyoto University, C1-1-209 Kyoto University Katsura, Nishikyo-Ku, Kyoto 615-8540, Japan H. Kawanaka Mie University, 577 Kurimamachiya, Tsu, Mie 514-8507, Japan
example, it is common to see hybrid vehicles (HV) on the roads in many countries. The fuel usage of some counties is getting decreased due to the significant popularity of HV. As a parallel technology, electric vehicles (EV) are also getting popular little by little and more development can be expected within several years. On the other hand, intelligent transportation systems (ITS) have also been deployed to reduce the traffic problems such as accidents and traffic jams. Most of ITS have been designed by applying information technology (IT) which have also been achieving significant developments in last few decades. ITS technologies can roughly be divided into two main categories as driver assistant systems and autonomous vehicles. Driver is supported detecting internal and external information by vehicle in the driver assistant systems, and all the decisions regarding to driving is made by vehicle detecting the same information in the autonomous driving. Many studies have widely been conducted to that information detection and most studies detect internal and external information of the vehicle installing the sensors and cameras on the vehicle. Some examples of ITS can be introduced as: car navigation, traffic light and traffic sign recognition [1], obstacle detection [2], pedestrian detection [3], vehicle to vehicle communication ([4] hompage), infrastructure to vehicle communication [5], and so on. Many
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