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