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In autonomous Vehicles technology Image segmentation was a major problem invisual perception. This image segmentation process is mainly used in medicalapplications. Here we adopted an image segmentation process to visualperception tasks for predicting the agents on the surrounding environment,identifying the road boundaries and tracking the line markings. Main objectiveof the paper is to divide the input images using the image segmentation processand Convolution Neural Network method for efficient results of visualperception. For Sampling assume a local city data-set samples and validationprocess done in Jupyter Notebook using Python language. We proposed this imagesegmentation method planning to standard and further the development ofstate-of-the art methods for visual inspection system understanding. Theexperimental results achieves 73% mean IOU. Our method also achieves 90 FPSinference speed and using a NVDIA GeForce GTX 1050 GPU.

Global Image Segmentation Process using Machine Learning algorithm & Convolution Neural Network method for Self- Driving Vehicles