License Plate(LP) symbols has been established with several methods. In this paper a new novel based algorithm suggested which is a amalgamation of connected component analysis method and Genetic algorithm. An Adaptive Threshold access is used to solve some illumination problem. Morphological procedure is an important process for most pattern recognition which remove noisy objects. Next Connected element analysis method is grouped pixel into labeled constituents. Extracted object from CCAT are riddled according to their widths and Heights. Genetic Algorithm phase has been announced to resolve the 2-D compound object uncovering problem. Fitness function has been selected by calculating objective distance. Object involving of a group of smaller objects and can be used to locate the compound object in an image given that its GRM values are nearly fixed. In this paper a survey is being carried out in the field of Automatic license plate localization. Automatic license plate recognition (ALPR) is to extract vehicle license plate information from an image or a sequence of images. The extracted information can be used with or without a database in many applications such as electronic payment systems, freeway and specific road monitoring systems for traffic surveillance. As a real-life application it has to quickly and successfully process license plates under different environmental conditions such as indoors, outdoors, day/night time.