To broaden the view point regarding the usage of the existing optimization technique under the visual computational applications for image processing, this task involves acquisition, pre-processing, extraction, segmentation and classification of high quality data from the real world in order to produce numerical or symbolic information. It can be used to recognize an object, tracking and motion. This also has high scope of improvement on its usage in the pattern recognition process. The pre-processing mainly involves the object localization and features the extraction of a set of training images that has to be separated. The role behind is to involve the collaboration of two optimization techniques that are particle swarm optimization and plant growth algorithm. It helps in realizing the problem with the best solution that may rise up. In case there is poor real-time ability in gesture recognition algorithm, an improved support vector machine classification algorithm of hand gesture recognition is proposed. In proposed system, the performance measure has highly improved in terms of the accuracy rate. The context of this article shows comparative analysis of hand gesture recognition system with particle swarm optimization and plant growth algorithm.