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In this paper, we investigate event classification that is specifically developed for use in consumer family photo collections. This domain is very different from news video collections that have been the focus of research in the area of scene content classification. We determine a set of broad event classes that are relevant to personal collections. We investigate the use of a variety of high-level...
We address document image classification by visual appearance. An image is represented by a variable-length list of visually salient features. A hierarchical Bayesian network is used to model the joint density of these features. This model promotes generalization from a few samples by sharing component probability distributions among different categories, and by factoring out a common displacement...
A simple pattern classification based noise identification method is proposed in this paper. The key idea involves isolation of some representative noise samples, and extraction of their statistical features for noise type identification. The isolation of representative noise samples is achieved using simple image filters and noise identification is performed using a few statistical and/or histogram...
This paper presents a robust, two-step method for edge and corner detection in noisy images. First it identifies the type of noise using a new pattern classification approach and then restores the image using a good restoration technique suitable for the type of noise identified. The types of noise considered here include uniform white, Gaussian white, speckle, and salt-and-pepper noise. From the...
A new technique to classify palm prints is proposed in this paper. A rectangular region of interest (ROI) containing only the heart line is extracted from palm print images obtained from a peg-free scanner. The ROI extraction is robust using boundary tracing and rotations based on our study of palm geometry. Preprocessing operations such as intensity normalization and smoothing are applied. Sobel...
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