Abstract
This paper presents a image processing technique for speed breaker, road marking detection and recognition. An Optical Character Recognition (OCR) algorithm was used to recognize traffic signs such as “STOP” markings and a Hough transform was used to detect line markings which serves as a pre-processing stage to determine when the proposed technique does OCR or speed breaker recognition. The stopline inclusion serves as a pre-processing stage that tells the system when to perform stop marking recognition or speed breaker recognition. Image processing techniques was used for the processing of features from the images. Local Binary Pattern (LBP) was extracted as features and employed to train the Support Vector Machine (SVM) classifier for speed breaker recognition. Experimental results shows 79%, 100% “STOP” sign and speed breaker recognitions respectively. The proposed system goes very well for the roads which are constructed with proper painting irrespective of their dimension.
Highlights
An intelligent transport system (ITS) is a global phenomenon, attracting worldwide interest from transportation professionals, the automotive industry, and political decision makers [1]
In light of that, [20] used Optical Character Recognition (OCR) to detect text-based traffic signs but in other to improve the accuracy of recognition, the OCR results from several frames were combined together by matching individual words through frames and using a weighted histogram of results, authors in [16] used “tesseract” an open source OCR engine to perform the character recognition because of its widespread approbation, its extensibility and flexibility, its community of active developers, and the fact that it “just works” out of the box
The stop marking recognition has an accuracy of 79.07% due to the inconsistencies on the fonts used in the marks
Summary
An intelligent transport system (ITS) is a global phenomenon, attracting worldwide interest from transportation professionals, the automotive industry, and political decision makers [1]. ITS provide transport solutions by utilizing state-of-the-art information and telecommunications technologies. It is an integrated system of people, roads and vehicles, designed to significantly contribute to improve road safety, efficiency and comfort, as well as environmental conservation through realization of smoother traffic by relieving traffic congestion according to Andersen and Sutcliffe [1]. DAS includes Driver drowsiness detection, Adaptive Cruise Control (ACC), Lane departure warning system, Traffic sign recognition, Wrong-way driving warning, automotive navigation system, and so on [2]. In this work, speed breakers with “STOP” traffic marking will be detected and recognized using image processing algorithms such as Local Binary Patten (LBP) and Optical Character Recognition (OCR) with template matching [7]. This article is separated into various segments; immediately following this section is section 2, which reviews existing literatures, section 3 explains the proposed methods for speed breaker detection and recognition, section 4 shows the results of the various experiments performed and performance evaluation and section 5 gives conclusion and future work
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