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Linear discriminant analysis (LDA) is one of the most popular methods for feature extraction and dimensionality reduction, but it may encounter the so called small sample size (SSS) problem when applied to high dimensional data analysis such as face recognition. Many two-stage methods were proposed to solve this problem such as Fisherfaces, Direct LDA and Null space LDA, but they are suboptimal from...
Recent studies have shown that convolutional networks can achieve a great deal of success in high-level vision problems such as objection recognition. In this paper, convolutional networks are used to solve a typical low-level image processing task, image segmentation. Here, the convolutional networks are trained using gradient descent techniques to solve the problem of segmenting the cell nuclei...
Automated segmentation of blood vessels in retinal images will help eye care specialists screen larger populations for vessel abnormalities. However, automated retinal segmentation is complicated by the fact that a number of vessels are very thin and the local contrast is low. We propose the radial projection method to locate the vessel centerlines which contains the thin vessels. Then the aggregate...
This paper proposes a new feature of fingerprint, called corner-cue. It is based on the curvature of fingerprint ridges. To extract the corner-cue, we first compute the curvature of fingerprint ridges and find the local maximum curvature points. Without regard to the high curvature points near minutiae, corner-cues are obtained. Corner-cues are further utilized in the matching stage to enhance the...
The representation of writing styles is a crucial step of writer identification schemes. However, the large intra-writer variance makes it a challenging task. Thus, a good feature of writing style plays a key role in writer identification. In this paper, we present a simple and effective feature for off-line, text-independent writer identification, namely wavelet domain local binary patterns (WD-LBP)...
The low-contrast and narrow blood vessels in retinal images are difficult to be extracted but useful in revealing certain systemic disease. Motivated by the goals of improving detection of such vessels, we propose the radial projection method to locate the vessel centerlines. Then the supervised classification is used for extracting the major structures of vessels. The final segmentation is obtained...
This paper proposes a new image retrieval method using non-separable discrete wavelets (NDWT) and local binary patterns (LBP). Compared with the traditional wavelet, the three high frequency sub-images generated by the non-separable wavelets can extract more information and do not extensively focus on the three special directions any more. Further, local image texture and their occurrence histogram...
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