This paper presents an efficient method for medical 2-D image enhancement technique using median and bottom hat filtering, that can also be used in image processing such as medical image reconstruction, image smoothing, feature extraction and image analysis. We present a comparison of these filters using the medical images. After filtering also the input image or actual image have some noise th...

This paper proposes a novel approach for smoothing surfaces represented by triangular meshes. The proposed method is a two-step procedure: surface normal smoothing through fuzzy vector median (FVM) filtering followed by vertex position update based on the least square error criteria. This paper applies the fuzzy ordering theory to the vector based data and introduces the fuzzy vector median. Th...

This paper proposes an improved hand dorsa (back of hand) pattern extraction algorithm for biometric personal authentication applications. The proposed method employs the existing database of near Infrared (IR) images of palm dorsal hand vein surface. The proposed system include: 1) Detection of Region of Interest from input image 2) Hand dorsa vein extraction by Contrast-Limited Adaptive Histo...

In this paper, we introduce a new mesh filtering method: a mesh median filter. This is an application of the median filter to smoothen 3-D noisy shapes given by triangle meshes. An algorithm of the mesh median filter is realized by applying the median filter to face normals on triangle meshes and updating mesh vertex positions to make them fit to the filtered normals. As an advanced modificatio...

Item-based collaborative filtering is becoming the most promising approach in recommender systems. It can predict an active user’s interest for a target item based on his observed ratings. With the user’s interests changing during interacting with collaborative filtering, the issue of concept drift is becoming a main factor impacting the accuracy of recommendation. Aiming at the issue of concep...

The difference between training and testing environments is the major reason of performance degradation of speech recognition. In this paper, to further decrease the mismatch, we apply temporal filtering, Auto-Regression and Moving-Average (ARMA) filtering or RelAtive SpecTrAl (RASTA) filtering, as a post-processor for the log-Energy dynamic Range Normalization-Cepstral Mean and Variance Normal...

Earlier research has shown that the problem of optimal weighted median filtering with structural constraints can be formulated as a nonconvex nonlinear programming problem in general. However, its high computational complexity and poor performance due to its nonconvex nature prohibit it from practical applications. In this paper, we shall show that the design problem can be formulated as a conv...

Median ltering is a powerful tool for reducing noise in images, particular for long-tailed noise distributions. However, the choice of lter mask is critical. The proper choice depends on the image and noise statistics, which are often unknown. We propose cross-validation as a method for selecting a median lter structure directly from the corrupted image data. This method requires no knowledge o...