Summary
As human beings, we perceive the world around us mainly through our eyes, and give what we see the status of “reality”; as such we historically tried to create ways of recording this reality so we could augment or extend our memory. From early attempts in photography like the image produced in 1826 by the French inventor Nicéphore Niépce (Figure 2.1) to the latest high definition camcorders, the number of recorded pieces of reality increased exponentially, posing the problem of managing all that information. Most of the raw video material produced today has lost its memory augmentation function, as it will hardly ever be viewed by any human; pervasive CCTVs are an example. They generate an enormous amount of data each day, but there is not enough “human processing power” to view them. Therefore the need for effective automatic image analysis tools is great, and a lot effort has been put in it, both from the academia and the industry. In this chapter, a review of some of the most important image analysis tools are presented.
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© 2009 Springer-Verlag US
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Falcoz, P. (2009). Simple Low Level Features for Image Analysis. In: Jeong, J., Damiani, E. (eds) Multimedia Techniques for Device and Ambient Intelligence. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-88777-7_2
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DOI: https://doi.org/10.1007/978-0-387-88777-7_2
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