02-05-2012, 11:48 AM
A Real-Time Face Recognition System Using Custom VLSI Hardware
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INTRODUCTION:
Humans are able to recognize faces effortlessly under all kinds of adverse conditions, but this simple task has been difficult for computer systems even under fairly constrained conditions. Successful face recognition entails the ability to identify the same person under different circumstances while distinguishing between individuals. Variations in scale, position, illumination, orientation, and facial expression make it difficult to distinguish the intrinsic differences between two different faces while ignoring differences caused by the environment. Even when acceptable recognition has been accomplished with a computer, the actual implementation has typically required long run times on high performance workstations or the use of expensive supercomputers. The goal of this work is to develop an efficient, real-time face recognition system that would be able to recognize a person in a matter of a few seconds.
TEMPLATE EXTRACTION AND NORMALIZATION:
Once the eyes are located, subsampled templates of the face, eyes, nose, and mouth are extracted (see Figure 4). The inter-ocular distance is taken as a scaling factor, and the inter-ocular axis
TEMPLATE CORRELATION WITH IMAGE DATABASE:
After the facial image of the user has been preprocessed to obtain the normalized templates, the templates are compared to those in an image database of known persons. Templates are compared to those in the database by a robust correlation process to compensate for possible registration errors. In particular, the template is compared to database images over a range of 25 different alignments corresponding to spatial shifts between +2 and -2 pixels in both the horizontal and vertical directions..
SYSTEM ARCHITECTURE:
The system hardware consists of an IBM PC 80486/DX2, a commercial frame grabber, video camera, and custom VLSI hardware (see Figure 6). The goal of the hardware system architecture is to extract the highest performance from those components.
CONCLUSIONS:
A real-time face recognition system can be developed by making effective use of the computing power available from an IBM PC 80486 and by implementing a special purpose VLSI image correlator. The complete system requires 2 to 3 seconds to analyze and recognize a user after being presented with a reasonable frontal facial image. This level of performance was achieved through careful system design of both software and hardware.