Autonomous car is a vehicle that can guide itself without human intervention. Various types of rudderless vehicles are being developed. Future systems where computers take over the art of driving. The problem is prior to being attention in an autonomous car for obtaining the high safety. Autonomous car need early warning system to avoid accidents in front of the car, especially the system can be used in the Highway location. In this paper, we propose a vision-based vehicle detection system for Autonomous car. Our detection algorithm consists of three main components: HOG feature extraction, KNN classifier, and vehicle detection. Feature extraction has been used to recognize an object such as cars. In this case, we use HOG feature extraction to detect as a car or non-car. We use the KNN algorithm to classify. KNN Classification in previous studies had quite good results. Car detected by matching about trining data with testing data. Trining data created by extract HOG feature from image 304 x 240 pixels. The system will produce a classification between car or non-car.
An autonomous car is a vehicle that can guide itself without human intervention. Various types of steeringless vehicles are being developed. The system of the future where computers take over the art of driving. The problem was before it became a concern in autonomous cars to get high safety. Autonomous cars need an early warning system to avoid accidents in front of the car, especially systems that can be used on highway locations. In this paper, we propose a vision-based vehicle detection system for vehicle detection in the form of cars. Our detection algorithm consists of two main components: Extraction of color features using GLCM values, and testing of 6 parameters of GLCM dissimilarity, correlation, homogeneity, contrast, ASM and energy. We use the SVM (Support Vector Machine) algorithm for the classification algorithm. The SVM (Support Vector Machine) classification in previous studies has had quite good results and has a fast computation time. Good accuracy results are found in the ASM feature and using an angle of 450
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