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We present a fast, automated, feature-based technique for classifying fingerprints. The technique extracts the singular points (delta and core points) in fingerprints obtained from directional histograms. The technique enhances the digitized image using adaptive clipping and image matching, finds the directional image by checking the orientations of(More)
This paper extends the watermarking method introduced in [1] in order to embed watermark data into fingerprint images, without corrupting their features. Two methods are proposed. The first method inserts watermark data after feature extraction thus prevents watermarking of regions used for fingerprint classification. The method utilizes an image adaptive(More)
For well over one-hundred years, several key factors have been well established in the study of number comparison, including mental number line, numerical distance effect, and effect of sensory representation on number processing. The purpose of this article is to put some of these studies together to discuss design parameters and research questions(More)
  • M. Ballan
  • 2004
In this work, the limited amount of mould images, which are captured by a microscopic camera, are classified. The enhancement algorithms are case dependent, because of the limited amount of data, but with too many classes. Firstly, a preprocessing algorithm is applied to enhance the data and then the features are extracted from enhanced data. Finally,(More)
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