Energy Efficient Data Processing in Visual Sensor Network

Abstract

Identifying moving objects from a video sequence is a fundamental and critical task in many computer

Untitled

“…The conventional object detection approaches in VSNs used various types of background subtraction techniques [12] to recognize the moving objects in the camera node's field-of-view. In such methods, camera nods send the captured/difference image that include objects to the base station [13,14]. While object detection methods with the camera nodes involvement perform preprocessing tasks after background subtraction and send only the bounding box of the objects or the useful information of them into the network [16,17,18,19].…”

“…In most of the machine vision applications [23], detecting the moving objects in the camera nodes' field-of view is one of the very important issues. To reduce the energy consumption of the network, Kenchannavar et al [13] suggested that the camera nodes must process the captured image, and then send the useful information to the base station.…”

“…The foreground image is reconstructed using the background image, difference image and the median filter [24] at the server and the energy consumed during reconstruction and transmission is calculated. Figure 2: Block Diagram for the Camera node and server [13] The results of authors' implementations show that the visual sensor network's bandwidth [25] in the cases that the captured images have been processed is efficient as compared to without processing the images, which in turn increase the network's lifetime [26]. However, in subtraction/reconstruction approaches, non-object pixels with zero value (black) are injected into the network, when the background subtraction result is sent to the base station.…”

“…The conventional object detection approaches in VSNs used various types of the background subtraction techniques [12] to recognize the difference between the background and foreground images. In such method, if the background subtraction result exceeds a pre-determined threshold, the camera node will detect moving objects within the monitoring area and sends the captured/difference image to the base station for recognition operations [13,14]. In visual sensor networks, the data communication cost is usually much higher than the image processing cost [15].…”

“…In background subtraction approaches for object detection in VSNs, each camera node subtracts the background and foreground images. If the difference between the background and foreground images exceeds a pre-determined threshold, the camera node will detect moving objects within its monitoring area and sends the foreground/difference image to the base station for recognition and classification operations [13,14].…”