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This research proposed an automatic student identification and verification system utilising off-line Thai name components. The Thai name components consist of first and last names. Dense texture-based feature descriptors were able to yield encouraging results when applied to different handwritten text recognition scenarios. As a result, the authors employed such features in investigating their performance...
Script identification is an important step in multi-script document analysis. As different textures present in text portion of a script are the main distinct features of the script, in this paper, we proposed a new algorithm for printed script identification based on texture analysis. Since local patterns is a unifying concept for traditional statistical and structural approaches of texture analysis,...
Recently, hyper-spectral facial image capturing techniques have opened a new door for creating innovative techniques aiming to improve these systems features. In our work, we have developed a verification approach based on Principal Component Analysis, and doing channel fusion (data fusion), in particular 5, 13, 14, 16, 24, 33, and 34 channels, reaching an Equal Error Rate of 97.37%; showing a good...
A method for Off-line Handwritten Signature Verification is described. It works at the global and local image level, measuring the stroke gray-level variations by means of wavelet analysys and statistical texture features. This method begins with a proposed background removal. Then Wavelet Analysis allows to estimate and alleviate the global influence of ink-type, and finally, properties of the Co-occurrence...
A method for Off-line handwritten signature verification is described in this paper. Recently, several papers have proposed pseudo dynamic methods based on the ink deposition process to discriminate between genuine and fake signatures. The major problem of those methods is the ink texture normalization in order to make the system invariable to the pen. The more extreme pen normalization is the binarization...
In this paper we present a biometric approach, based on lip shape. We have performed an image preprocessing, in order to detect the face of a person image. After this, we have enhanced the lips image using a color transformation, and next we do its detection. The parameterization is based on lips contour points. Those points have been transformed by a Hidden Markov Model (HMM) kernel, using a minimization...
A hand profile characterisation approach for biometric identification with contactless hand image acquisition is evaluated. The approach models the shapes of fingers with Point Distribution Models (PDMs), which consist of a mean shape and a number of eigenvectors which describe the main modes of variation of the shape class. The weighted PDM eigenvectors that capture the variation between the input...
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