Dynamic Prioritization of Image Blocks in Sensor Network for Border Survelliance

In the field of surveillance, several algorithms are developed to extract meaningful information from an image captured via a camera. In the presence of intrusion event, these cameras will transmit those captured images to the sink node via other intermediate nodes. Since, WSNs operate with limited resources, efficient utilization of resource is needed while processing and transporting images. Since the node does not need whole image data are mandatory. Prioritization is one of the methods to utilize the available resource. It will prioritize images from its macro-blocks dynamically. Here the camera is attached in a sensor node which forms Wireless Multimedia Sensor Networks (WMSN). Its employs an encoding scheme at the source node by naming the blocks as “important” or “not-important” based on the information they contain. Here image texture feature and spectral information is used as priority measures to weight importance of macro-blocks using their textural GLCM properties. Experimental results disclose that the priority encoding scheme adapts itself to the application's quality requirements while reducing the required bandwidth comparatively.