Speed Breakers, Road Marking Detection and Recognition Using Image Processing Techniques

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.

Development of an Intelligent Road Anomaly Detection System for Autonomous Vehicles

“…The image processing was used in the development of a speed breaker and road marking detection system in [28]. The technique involved using image processing for speed breaker and road marking detection.…”

Museum Relic Image Detection and Recognition Based on Deep Learning

“…There is no need to search too much for the optimal threshold when identifying cultural relic targets, so as to ensure high efficiency. In the study, other types of feature extraction methods are used for comparative analysis [ 30 ], and the results obtained are shown in Table 3 .…”