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In this paper, we present a new face recognition algorithm based on weighted deep face learning. Our proposed method composes of two steps: face detection and face feature extraction. The aim of face detection is to find an accurate face position. The face alignment is then applied by finding the facial landmarks in the face rectangle. With the help of face alignment the error rate of face recognition...
A new method for fast bilateral filtering with texture‐preserving properties is presented. In general, the texture area is composed of several tiny regions that have almost similar intensity, and therefore bilateral filtering combines similar gray scales of the texture area to form a smooth region. Adaptive boundary filtering solves this problem by using image segmentation to define a new weighting...
In this paper, we present the encoding produces technique for texture recognition. This produces are developed with the purpose to replaced the previous method. Firstly, we encode image informations by VTT (Volume Trace Transform), and trace functionals are chosen by RL (Reinforce Learning). The number of VTT results are extracted by the amount of trace functionals. Secondly, we present P-DFT (Plus-Discriminant...
This paper presents the method of image texture recognition by Volume Trace Transform-VTT, based on several Trace function. All of 10 trace functions will be selected by the reinforcement learning process and constructed to produce noticeable features. The next process is to sum the results of each function together by “NDFT - Neighbor Discriminant Feature Transform”, this process will all the results...
In this paper, we present a new adaptive boundary filtering which is an improvement of the bilateral filtering algorithm. Bilateral filtering is an algorithm that is used for smoothing and preserving the edges in an image. This algorithm has proper capability when using with normal surface that have less number of regions. For texture area, many complicated regions are packed together e.g., hair and...
In recent years, particle filters have been applied with great success to 2D and 3D tracking problems. We presents the tracking of two hands based on a statistical model using only a skin colour feature with particle filtering for gesture recognition. The tracking scheme employs the reliability measurement derived from the particle distribution which is used to adaptively weight the skin-pixel colour...
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