International journal of computer science & information Technology (IJCSIT) Vol.2, No.5, October 2010 DOI : 10.5121/ijcsit.2010.2511 151 ENERGY EFFICIENT DATA PROCESSING IN VISUAL SENSOR NETWORK Harish. H. Kenchannavar 1 , Sushma. S. Kudtarkar 2 , U. P. Kulkarni 3 1 Dept of Computer Science & Engineering Gogte Institute of Technology, Belgaum India harish_14@rediffmail.com 2 Dept of Computer Science & Engineering Gogte Institute of Technology, Belgaum India sushmakudtarkar@gmail.com 3 Dept of Computer Science & Engineering SDMCET, Dharwad India upkulkarni@yahoo.com ABSTRACT Identifying moving objects from a video sequence is a fundamental and critical task in many computer- vision applications. After the images are captured they must be processed and then sent to the server. In this paper we characterize the energy consumption of a visual sensor network testbed. Each node in the testbed consists of a “single-board computer”, equipped with a network card and a webcam. We assess the energy consumption of activities representative of the target application (e.g., perimeter surveillance) using a benchmark that runs (individual and combinations of) “basic” tasks such as processing, image acquisition, and communication over the network. In our characterization, we consider the various hardware states that the system switches through as it executes these benchmarks, e.g., different radio modes (sleep, idle, transmission, reception), and webcam modes (off, on, and acquiring image) using Matlab Sensor Node and Lifetime simulator. We report the energy utilized by each frame during transmission at the server. Here we can analyze the energy consumed with processing and without processing of video frames. KEYWORDS Surveillance, Motion Detection, Energy Consumption, Reconstruction. 1. INTRODUCTION Visual sensor networks are networks of wireless camera-nodes, where the camera-node consists of the image circuitry, a processor, and a wireless transceiver. The network generally consists of the cameras themselves, which have some local image processing, communication and storage capabilities, and possibly one or more central computers, where image data from multiple cameras is further processed and fused (this processing may, [1],[2] however, simply take place in a distributed fashion across the cameras and their local controllers). Visual sensor networks also provide some high-level services to the user so that the large amount of data can be distilled into information of interest using specific queries. Visual sensor networks suitable for use in