A proposed feature extraction algorithm for handwriting Arabic words. The proposed method uses a 4 levels discrete wavelet transform (DWT) on binary image. sliding window on wavelet space and computes the stander derivation for each window. The extracted features were classified with multiple Support Vector Machine (SVM) classifiers. The proposed method simulated with a proposed data set from different writers. The experimental results of the simulation show 94.44% recognition rate.

     The aims of visible watermarking are to prevent the illegal copying of videos and images and to avoid the theft and unauthorized advertisement of the legitimate owners' content. The visible watermark is distinguishable with the naked eye. This makes it easily removed by an attacker. This paper proposes an anti-removable visible logo by double embedding using the discrete wavelet transform (DWT) and a chaotic map. The main purpose of this method is to prevent the removal attack and restore the original video without information loss after the logo is legally removed. DWT is used for both the cover area and the logo to embed sub-bands of information from the cover area into sub-bands of the logo. The main idea of using a chaotic m

     Today, the use of iris recognition is expanding globally as the most accurate and reliable biometric feature in terms of uniqueness and robustness. The motivation for the reduction or compression of the large databases of iris images becomes an urgent requirement. In general, image compression is the process to remove the insignificant or redundant information from the image details, that implicitly makes efficient use of redundancy embedded within the image itself. In addition, it may exploit human vision or perception limitations to reduce the imperceptible information.
     This paper deals with reducing the size of image, namely reducing the number of bits required in representing the

Some problems want to be solved in image compression to make the process workable and more efficient. Much work had been done in the field of lossy image compression based on wavelet and Discrete Cosine Transform (DCT). In this paper, an efficient image compression scheme is proposed, based on a common encoding transform scheme; It consists of the following steps: 1) bi-orthogonal (tab 9/7) wavelet transform to split the image data into sub-bands, 2) DCT to de-correlate the data, 3) the combined transform stage's output is subjected to scalar quantization before being mapped to positive, 4) and LZW encoding to produce the compressed data. The peak signal-to-noise (PSNR), compression ratio (CR), and compression gain (CG) measures were used t

        The wavelet transform has become a useful computational tool for a variety of signal and image processing applications.

     The aim of this paper is to present the comparative study of various wavelet filters. Eleven different wavelet filters (Haar, Mallat, Symlets, Integer, Conflict, Daubechi 1, Daubechi 2, Daubechi 4, Daubechi 7, Daubechi 12 and Daubechi 20) are used to compress seven true color images of 256x256 as a samples. Image quality, parameters such as peak signal-to-noise ratio (PSNR), normalized mean square error have been used to evaluate the performance of wavelet filters.

   In our work PSNR is used as a measure of accuracy performanc

     In today's world, digital image storage and transmission play an essential role,where images are mainly involved in data transfer. Digital images usually take large storage space and bandwidth for transmission, so image compression is important in data communication. This paper discusses a unique and novel lossy image compression approach. Exactly 50% of image pixels are encoded, and other 50% pixels are excluded. The method uses a block approach. Pixels of the block are transformed with a novel transform. Pixel nibbles are mapped as a single bit in a transform table generating more zeros, which helps achieve compression. Later, inverse transform is applied in reconstruction, and a single bit value from the table is rem

The data compression is a very important process in order to reduce the size of a large data to be stored or transported, parametric curves such that Bezier curve is a suitable method to return gradual change and mutability of this data. Ridghelet transform solve the problems in the wavelet transform and it can compress the image well but when it uses with Bezier curve, the equality of compressed image become very well. In this paper, a new compression method is proposed by using Bezier curve with Ridgelet transform on RGB images. The results showed that the proposed method present good performance in both subjective and objective experiments. When the PSNR values equal to (34.2365, 33.4323 and 33.0987), they were increased in the propos

This article presents a polynomial-based image compression scheme, which consists of using the color model (YUV) to represent color contents and using two-dimensional polynomial coding (first-order) with variable block size according to correlation between neighbor pixels. The residual part of the polynomial for all bands is analyzed into two parts, most important (big) part, and least important (small) parts. Due to the significant subjective importance of the big group; lossless compression (based on Run-Length spatial coding) is used to represent it. Furthermore, a lossy compression system scheme is utilized to approximately represent the small group; it is based on an error-limited adaptive coding system and using the transform codin