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We introduce a facial expression recognition method, which incorporates a weight to the Local Binary Pattern (LBP), and generates solid expression features. Furthermore, we use Adaboost to select a small set of prominent features, which is used by the Support Vector Machine (SVM) to classify facial expressions efficiently. Experimental results demonstrate that our method outperforms the state-of-the-art...
In this paper we present an effective method for image contrast enhancement with a mapping function that improves both the brightness and fine details of the input image. With the global transformation function it combines an intensity-pair distribution based expansion function from each image block to control the enhancement of image details, which the global transformation function alone may fail...
Image enhancement mostly means handling with the contrast of the pixels. However, conventional histogram equalization (HE) methods works based on the global histogram information only. Hence they often make an overall enhancement of the whole image without taking any intensive care of the spatial relationship among the pixels. This often leads to a number of annoying artifacts. In this paper we propose...
A new approach for skin region segmentation is proposed. It uses color distance map (CDM) and an algorithm based on the property of flow of water. The CDM itself is a grayscale image, which makes the algorithm very simple. However, it is still capable of providing color information based on which some skin and non-skin seed regions can be determined reliably. Then a water-flow based procedure determines...
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