Centrog Feature technique for vehicle type recognition at day and night times

التفاصيل البيبلوغرافية
العنوان: Centrog Feature technique for vehicle type recognition at day and night times
المؤلفون: Irhebhude, Martins E., Odion, Philip O., Chinyio, Darius T.
سنة النشر: 2016
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition
الوصف: This work proposes a feature-based technique to recognize vehicle types within day and night times. Support vector machine (SVM) classifier is applied on image histogram and CENsus Transformed histogRam Oriented Gradient (CENTROG) features in order to classify vehicle types during the day and night. Thermal images were used for the night time experiments. Although thermal images suffer from low image resolution, lack of colour and poor texture information, they offer the advantage of being unaffected by high intensity light sources such as vehicle headlights which tend to render normal images unsuitable for night time image capturing and subsequent analysis. Since contour is useful in shape based categorisation and the most distinctive feature within thermal images, CENTROG is used to capture this feature information and is used within the experiments. The experimental results so obtained were compared with those obtained by employing the CENsus TRansformed hISTogram (CENTRIST). Experimental results revealed that CENTROG offers better recognition accuracies for both day and night times vehicle types recognition.
Comment: 14 pages, 8 figures, Journal article
نوع الوثيقة: Working Paper
DOI: 10.5121/ijaia.2016.7604
URL الوصول: http://arxiv.org/abs/1612.00645
رقم الأكسشن: edsarx.1612.00645
قاعدة البيانات: arXiv