Abstract
Image processing is one of the most important features for vision-based robotic and being used in various applications to increase productivity. Various researchers reported issues computation problem to detect objects in low cost device such as vision-based robotic car. In the fast-paced development of technology, a system that runs automatically with the right results is essential to the completion of a job. This study aims to propose an effective multithreading for road sign recognition. We implemented multithreading algorithm for train and detector processes in SVM to utilise the multicore CPU and evaluate in various condition on by a Raspberry Pi platform. It aims to solve the real-time computation issue using Pi camera. Experimental results show significant improvement of performance to the detection accuracy. In conclusion multithreading significantly improve the detection performance using Raspberry Pi processors with various image resolution and number of SVM model.
Highlights
Image processing is one of the most important features for vision-based robotic and being used in various applications to increase productivity
This study focus on about vision-based robotic cars with improvements in multithreading and image processing
This study is divided into five phases which contains collection of data, annotation, training, detection using support vector machine (SVM) and improvement using multithreading procedure
Summary
Image processing is one of the most important features for vision-based robotic and being used in various applications to increase productivity. One of the interesting topic is object recognition which has been evolved drastically. Due to large resource consumption for computation, multithreading method are one the way to optimize using multi-tasking process and fasten the computation in real-time application. Timing is an important factor in image processing because the delay in time or delivery of an image template would cause many issues in the final decision. This lead to adoption the concept of multithreading in low cost computing device such as Raspberry Pi so that the results of recognition are accurate
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