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Title: Image Processing
Description: Image Processing

The growth of the Electronic Media, Process Automation and especially the outstanding growth of attention to national and personal security in the past few years have all contributed to the growing need of being able to automatically detect features and occurrences in pictures and video streams on a massive scale, without the need for human eye intervention and in real time. To date, all technologies available for such automated processing have come short of being able to supply a solution that is both technically viable and cost-effective.

This white paper details the basic ideas behind a novel, patent-pending technology called Image Processing over IP networks (IPoIP). As its name implies, IPoIP provides a solution for automatically extracting useful data from a large number of simultaneous image (video or still) inputs connected to an IP network, but unlike other existing methods, does so at reduced costs without compromising reliability. The document will also outline the existing image-processing architectures and compare them to IPoIP. Ending this document will be a short chapter detailing several possible implementations of IPoIP in existing applications.

Introduction

A tremendous amount of research effort has been put into the ability to extract meaningful data out of captured images (both video and still) in the past years. As a result, a large number of proven algorithms exist both for real-time and offline applications, algorithms that are implemented on platforms ranging from pure software to pure hardware. These platforms, however, are generally designed to deal with a relatively small number of simultaneous image inputs (in most cases actually no more than one). They are designed in one of two main architectures: Local Processing and Server Processing.

Local Processing Architecture

This is by far the most commonly available system architecture for image processing. The main idea behind it is that all the processing is done at the camera location by a processing unit, and the results are then transmitted through a network connection to the monitoring area. The processing unit is usually PC based for the more complex solutions but the recent growing trend is to move the processing to standalone boxes based on a DSP or even an ASIC. It performs the entire image-processing task and outputs a suitable message to the network when an event is detected. Also residing at the location of the camera is a video encoder that is used for remotely viewing the video through the IP network. It can be configured to transmit the video at varying qualities depending on the available bandwidth. The video is transmitted using standard video compression techniques such as MJPEG, MPEG-4 and others. When cost is less of an issue, this architecture provides an adequate solution for running a single type of algorithm per camera. However, when the number of cameras increases and a more robust solution is needed (which is in many times the case), this solution falls short due to the following reasons:

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