Microcalcifications are small densities that appear as bright spots on mammograms. Its detection plays a very important role in breast cancer detection at early stages in digitized mammographic images. This paper presents an approach for computer aided detection of microcalcifications. The main idea of the proposed approach is to apply wavelet analysis followed by a non-linear transformation fu...

This paper presents a DWT-DCT-SVD based hybrid watermarking method for color images. Robustness is achieved by applying DCT to specific wavelet sub-bands and then factorizing each quadrant of frequency sub-band using singular value decomposition. Watermark is embedded in host image by modifying singular values of host image. Performance of this technique is then compared by replacing DCT by Wal...

Feature extraction is a collection of the necessary detailed information from given source, which holds for further analysis. The quality fused image depends on many parameters, particularly its directional selectivity and shift-invariance. On other hand, traditional wavelet-based transforms produce ringing distortions artifacts due to poor directionality shift invariance. Dual-Tree Complex Wav...

In this research an innovative fully automated 3D face compression and recognition system is presented. Several novelties are introduced to make the system performance robust and efficient. These novelties include: First, an automatic pose correction and normalization process by using curvature analysis for nose tip detection and iterative closest point (ICP) image registration. Second, the use...

In this paper, we propose a new scheme of dual watermarking by applying discrete wavelet transform and principal component analysis. For the embedding, we identify two best sub bands of wavelet transform by considering the intensity variance of each sub band. Two watermarks are embedded within the selected sub bands with respect to their principal components. Using dual watermark improves robus...

The amplitude of nuclear magnetic resonance (NMR) longing signal general is very small while the signal to noise ratio (SNR) is also very low, so de-noising NMR signal before T2 spectrum inversion is necessary and important. In this paper, an improved de-noising algorithm based on wavelet transform is put forward. The main idea of this improved algorithm is that NMR signal is divided to several...

Wavelet transform is a type of signal representation that can give the frequency content of the signal at a particular instant of time. The Objective of Compression is to reduce the memory and efficient use of bandwidth. JPEG-2000 is an emerging standard for still image compression. Image compression must not only reduce the necessary storage and bandwidth requirements, but also allow extractio...

Images have large data quantity, for storage and transmission of images, high efficiency image compression methods are under wide attention. In this Paper we proposed and implemented a wavelet transform and neural network model for image compression which combines the advantage of wavelet transform and neural network. Images are decomposed using Haar wavelet filters into a set of sub bands with...

Speech compression is an area of digital processing that is focusing on reducing bit rate of the speech signal for transmission or storage without significant loss of quality. The focus of this paper is to compress the digital speech using wavelet transform. The uncompressed digital speech requires huge amount of memory. The main idea behind the speech compression algorithm is to represent this...

Within this paper a new feature extraction techniques is presented which uses wavelet analysis and fractal theory for image recognition. The proposed method reduces the dimensionality of a twodimensional pattern by way of a central projection approach, and thereafter, performs Daubechies' wavelet transformation on the derived one-dimensional pattern to generate a set of wavelet transformation s...