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Automatic classification of Human Epithelial Type-2 (HEp-2) specimen patterns is an important yet challenging problem in medical image analysis. Most prior works have primarily focused on cells images classification problem which is one of the early essential steps in the system pipeline, while less attention has been paid to the classification of whole-specimen ones. In this work, a specimen pattern...
Tattoos have been increasingly used as a discriminative soft biometric for people identification, such as criminal and victim identification in forensics investigation and law enforcement. However, automatic detection of tattoo images and accurate localization of the regions of interest are challenged by the large variations in artistic composition, color, shape, texture, location on the body, local...
We propose a method to recognize pollen grains using a two-stage classifier. First, texture classification categorizes the pollen grains into sub-groups. Then, a final classification of individual pollen types is done by segmenting the image int multiple layers of regions for each pollen image. The main novelty in our method is threefold: (1) Adopting two successive classification stages. (2) Combining...
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