Region-based color image segmentation is elementary steps in image processing and computer vision. Color image segmentation is a region growing approach in which RGB color image is divided into the different cluster based on their pixel properties. The region-based color image segmentation has faced the problem of multidimensionality. The color image is considered in five-dimensional problems, in which three dimensions in color (RGB) and two dimensions in geometry (luminosity layer and chromaticity layer). In this paper, L*a*b color space conversion has been used to reduce the one dimension and geometrically it converts in the array hence the further one dimension has been reduced. This paper introduced an improved algorithm MMFO (Modified Moth Flame Optimization) Algorithm for RGB color image Segmentation which is based on bio-inspired techniques for color image segmentation. The simulation results of MMFO for region based color image segmentation are performed better as compared to PSO and GA, in terms of computation times for all the images. The experiment results of this method gives clear segments based on the different color and the different no. of clusters is used during the segmentation process.

Road transportation is the most common and oldest mode of transportation. It provides quick connectivity to small businesses having customers nearby areas, transportation of perceivable products in nearby markets. Not only the nearby market, also for international market supply transferring goods from the supply unit to the railway station, ports, or airports. Also, from day to day life commute from home to the office for a service class person, from home to schools/colleges for students, commuting to hospitals, banks, malls are done by road transportation only. It has an essential contribution to economic growth. Although road transportation is an essential and most common mode of connectivity, it has a higher probability of road crashes than any other transportation mode. These results a lot of injuries, deaths in every year and every city. Government has lot of road safety protocols, rules, and regulations to prevent road accidents. Every year government is spending a lot for road safety. Not only government car/vehicle manufacture keep on redesigning the vehicle with multiple inbuilt safety equipment’s. This paper is proposing a device with a key feature of lane detection. The device is featured with monitoring of engine, tires and other peripherals. The device can be mounted in vehicle, and can make an ordinary vehicle to semi-smart vehicle. This paper explains a feature of the device that is lane detection. An identification of tracks and obstruction on streets is not an easy task to detect with proximity sensors and an IR sensor. So that a digital image processing based lane detection technique had been implemented in this paper. This technique is very efficient to detect the road path and obstructions on the street on different scope of ecological conditions under which these frameworks work: rain, shadow, daylight, day, night, haze and so forth.