A Survey for Building Real-time Vision based Road Detection Model
Devyani Kalghatgi1, Digambar Kulkarni2

1Devyani Kalghatgi, Department of Computer Science Engineering, KLS’s Gogte Institute of Technology, Belagavi (Karnataka), India.
2Digambar Kulkarni, Department of Computer Science Engineering, KLS’s Gogte Institute of Technology, Belagavi (Karnataka), India.
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 197-201 | Volume-8 Issue-6, April 2019 | Retrieval Number: F3639048619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: With every passing day around the year nearly thousands of lives across the world are lost due to mishaps on the roads. Furthermore, many other people are injured. The finest way to handle such a problem is to build a road detection mechanism. It plays an ultra-critical part of various vision navigation systems for putting together an intelligent transport or vehicle guidance systems. In recent times number of computer vision based independent navigation systems have been presented by various researches in various social and industrial applications. Thus, this paper conducts a voluminous survey on different state-of-art model for designing road edge detection model. From the survey it can be observed that these methods are broadly classified into model driven, feature driven and activity driven. Further, the existing model for detecting the outcome is substantially affected by the presence of noise in an image (due to fog and other environmental condition). To address such a research hurdle, this paper gives a research direction for modeling efficient mechanisms for detecting the edges of the road identifying exact location, speed and size of obstacles and direction of road extension.
Keyword: Autonomous Robots, Computer Vision, Edge Detection, Intelligent Transport System.
Scope of the Article: Software Domain Modelling and Analysis