We discuss features extracted from a wavelet packet decomposition for image classification. Statistical features computed from wavelet packet coefficients are compared to structural features which are derived from an image dependent wavelet packet decomposition subband structure. Primary application area is the classification of pit pattern structures in zoom-endoscopic colon imagery, while res...

This paper demonstrates a method and system for north finding with a low-cost piezoelectricity accelerometer based on the Coriolis acceleration principle. The proposed setup is based on the choice of an accelerometer with residual noise of 35 ng•Hz-1/2. The plane of the north finding system is aligned parallel to the local level, which helps to eliminate the effect of plane error. The Coriolis ...

Extended Abstract Wavelet packets 14] represent a generalization of the method of multires-olution decomposition and comprise the entire family of subband coded (tree) decompositions 11, 15]. Whereas in the wavelet case the decomposition is applied recursively to the coarse scale approximations (leading to the well known (pyramidal) wavelet decomposition tree), in the wavelet packet decompositi...

-In this paper, we propose an efficient method for rearranging the wavelet packet coefficients of an image to form hierarchical trees, by which the well known SPIHT algorithm can be applied. For images with textures, the high frequency wavelet coefficients are likely to become significant after several code passes of SPIHT, which degrades substantially the coding performance. As a result, the h...

In this paper, we propose an efficient method for rearranging the wavelet packet coefficients of an image to form hierarchical trees, by which the well known SPIHT algorithm can be applied. For images with textures, the high frequency wavelet coefficients are likely to become significant after several code passes of SPIHT, which degrades substantially the coding performance. As a result, the hi...

For using process operational data to realize process monitoring, kinds of improved Principal Components Analysis (PCA) have been applied to cope with complex industrial processes. In this paper, a novel nonlinear wavelet packet PCA (NLWPPCA) method, which combines input training network with wavelet packet PCA, is proposed. Wavelet packet PCA integrates ability of PCA to de-correlate the varia...

We present frequency and spatial adaptive packet wavelet coder implemented with Cellular Neural Network architecture. This paper also demonstrates how the cellular neural universal machine (CNNUM) architecture can be extended to image compression. The packet wavelet coder performs the operation of image compression, aided by CNN architecture. It uses the highly parallel nature of the CNN struct...