Research of the Wavelet Transform Printing Forgery Prevention Algorithm Based on Chaotic Characteristics

From the prospect of the printing forgery prevention technology, this paper systematically analyzed the principles of digital watermark in printing forgery prevention technology, based on this, it proposed wavelet transforming printing forgery prevention algorithm based on chaotic characteristics, in this paper, by using digital watermark image scrambling technology based on chaotic mapping to encrypt the wavelet transforming coefficient, then choose the different K value in chaotic mapping and the size of the scrambling image to combine the the cryptography technology and the wavelet transforming technology for resisting the various printing forgery attack effectively. In the end, the author made a detailed design about the wavelet transform printing forgery prevention system which based on chaotic characteristics and put it into fact by VC++, then validated the algorithm by experimental result, then compared it to the traditional watermark algorithm from the aspect of the image compression and anti attack ability to prove the stability and robustness of the algorithm this paper proposed.

Targeting on Enhancing 2D Aerial Image Information by Technology of Unsharp Masking

To obtain image enhancement by getting detail texture features rich through the subtraction between the original graph and low-frequency graph, utilizing the wavelet decomposition technique, separating the components of high frequency and low frequency in the 2D (two-dimensional) aerial image, filtering the low frequency subgraph, and retaining only the low-frequency part. Practice has proved that the unsharp masking algorithm of wavelet transforming has obvious superiority over the traditional algorithm. The algorithm can separate characteristics of different resolution details, adjust the filter window size, make the wavelet components of different scales enhanced, the detail more clear, get a strong sense of layer and good enhancement effect.

Fault Diagnosis Research for Electrical Starting System of Hybrid Electric Vehicle Based on Wavelet Transform

The non-stationary characteristics of starting motor’s current can effectively reflect the faults of vehicle’s electrical starting system. Taking the working current of starting motor as original signal, the signal’s singular points were detected by wavelet transforming. And through comparing the singularity characteristics with normal state, the common faults of starting system were identified accurately. The practical application to a certain type of hybrid electric vehicle shows that the proposed method based on wavelet singularity analysis can effectively extract the key characteristics of starting current signal and realize the identification of electric starting system’s common faults.

The Method of Average Modulus Based on Wavelet Transform to Recognize the Sequence Stratigraphy Boundaries with Logging Curves

Choose a wavelet to transform the logging curves, which can obtain a series of scale and depth corresponding to wavelet coefficients. From the view of fourier series expansion and spectrum energy, the wavelet coefficients of optimal scale should be the largest proportion of total spectral energy. Based on the theory above, method of average modulus based on wavelet transform is put forwarded. Find the optimal scale factor through wavelet transforming of logging curves, and establish a correspondence between oscillations characteristic of wavelet coefficients curve of the optimal scale factor and sequence stratigraphy boundaries. This method provides a new way to recognize sequence stratigraphy boundaries.

Edge Detection Based on Wavelet Transform and Fusion

To pick-up information from the image, the pretreatment towards the image is necessary. Based on the contrast from the traditional edge detection, the theory of wavelet transform is introduced and studied. Then the image is smoothed through wavelet transforming. Meanwhile, the edge information of the image is intensified using the transforming. This paper proposes a new mage fusion method based on wavelet transform. Across the computer simulation, it’s educed that the result of edge detection based on wavelet transform is much better than the traditional edge detection.