Abstract
Vehicle logo detection from images captured by surveillance cameras is an important step towards the vehicle recognition that is required for many applications in intelligent transportation systems and automatic surveillance. The task is challenging considering the small target of logos and the wide range of variability in shape, color, and illumination. A fast and reliable vehicle logo detection approach is proposed following visual attention mechanism from the human vision. Two prelogo detection steps, that is, vehicle region detection and a small RoI segmentation, rapidly focalize a small logo target. An enhanced Adaboost algorithm, together with two types of features of Haar and HOG, is proposed to detect vehicles. An RoI that covers logos is segmented based on our prior knowledge about the logos’ position relative to license plates, which can be accurately localized from frontal vehicle images. A two-stage cascade classier proceeds with the segmented RoI, using a hybrid of Gentle Adaboost and Support Vector Machine (SVM), resulting in precise logo positioning. Extensive experiments were conducted to verify the efficiency of the proposed scheme.
Highlights
With the development of traffic infrastructures and the automobile industry, intelligent transportation system (ITS) is becoming ever more significant
Within a detected vehicle image, the region of interest (RoI) will be segmented based on the license plate position
With the increasing demand for security awareness and widespread use of surveillance cameras, there is an urgent need to develop vehicle identification and classification technologies to automatically identify the manufacturer of vehicles through recorded images
Summary
With the development of traffic infrastructures and the automobile industry, intelligent transportation system (ITS) is becoming ever more significant. As an important part of ITS, automatic vehicle recognition (AVR) has been attracting a significant amount of attention in the recent years due to its commercial value and practical significance in road traffic monitoring and management. AVR is pertinent to many intelligent surveillance applications [1,2,3,4,5,6]. The conventional vehicle registration plate recognition techniques are insufficient to identify the vehicle. This is relevant when license plate information is unreliable, for example, when the license plate is forged
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