Architecture for processing fingerprint images

Image analysis – Image transformation or preprocessing – General purpose image processor

Reexamination Certificate

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C382S124000

Reexamination Certificate

active

06795592

ABSTRACT:

BACKGROUND
This disclosure is related to classification and feature extraction.
Feature extraction is a current area of research and development in digital image processing and computer vision, particularly in areas of development involving feature based pattern recognition. Many image recognition, image detection, and biometrics applications, for example, have been developed based on techniques of feature extraction and pattern recognition. Feature extraction in fingerprint images has unique aspects compared to general purpose image processing applications at least in part due to its special topological characteristics. Most of the approaches proposed in the literature transform a fingerprint image into a binary image based at least in part on convolution of the image with a filter coupled with certain variants of thresholding. However, this approach has several disadvantages, such as computational intensity and the inability to robustly address noisy images. Moreover, most of the methods in the literature are slow, complicated, and difficult to implement in hardware. A need, therefore, exists for other processing techniques and architectures to support such techniques.


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Ratha, et al., “Adaptive Flow Orientation-Based Feature Extraction in Fingerprint Images”, XP 000539636, Pattern Recognition, vol. 28, No. 11, Nov. 28, 1995, pp. 1657-1671.

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