In this paper, an algorithm for reconstruction of a completely lost blocks using Modified
Hybrid Transform. The algorithms examined in this paper do not require a DC estimation
method or interpolation. The reconstruction achieved using matrix manipulation based on
Modified Hybrid transform. Also adopted in this paper smart matrix (Detection Matrix) to detect
the missing blocks for the purpose of rebuilding it. We further asses the performance of the
Modified Hybrid Transform in lost block reconstruction application. Also this paper discusses
the effect of using multiwavelet and 3D Radon in lost block reconstruction.

Steganography is a mean of hiding information within a more obvious form of
communication. It exploits the use of host data to hide a piece of information in such a way
that it is imperceptible to human observer. The major goals of effective Steganography are
High Embedding Capacity, Imperceptibility and Robustness. This paper introduces a scheme
for hiding secret images that could be as much as 25% of the host image data. The proposed
algorithm uses orthogonal discrete cosine transform for host image. A scaling factor (a) in
frequency domain controls the quality of the stego images. Experimented results of secret
image recovery after applying JPEG coding to the stego-images are included.

Digital image is widely used in computer applications. This paper introduces a proposed method of image zooming based upon inverse slantlet transform and image scaling. Slantlet transform (SLT) is based on the principle of designing different filters for different scales.

      First we apply SLT on color image, the idea of transform color image into slant, where large coefficients are mainly the   signal and smaller one represent the noise. By suitably modifying these coefficients , using scaling up image by  box and Bartlett filters so that the image scales up to 2X2 and then inverse slantlet transform from modifying coefficients using to the reconstructed image .

  &nbs

The lexical connotation is one of the types of connotation that linguists have dealt with, and stipulated in their studies, meaning access to the real meanings of the words, that the lexicon can address after tracing the real meaning of the metaphorical meanings, if any, and this is known to the semantics additional significance, and the rhetorical meaning Figuratively.
The miraculous Qur'an in its systems often refers to the metaphorical uses of the words as well as the real use. The significance of the words in the Holy Qur'an came in a variety of contexts, making each word a special significance that belongs to it exclusively. This is the miracle of the Holy Qur'an. The coming of the slow walk, with its eight words (came, came, cam

In pre- Islamic poetry, there are a lot of words that indicate
peacefulness of one sort of another, in addition to the inspirations of semantic
modeling in which the poet sets himself in various horizons.
Among these words: brother, comrade, friend, companion, lover,
people, prince, home, land, country, blessing, honesty, contract, company,
justice, thankfulness, forgiveness, pardoning, guest, goodness, faithfulness,
silence, death, peace,….
In addition, there are their derivatives from various aspects that indicate
peacefulness either directly or indirectly.

Abstract.. Quantitative characteristics of the surrounding world’s entities are expressed by the specific words – logical quantifiers. In a language, quantifiers are represented by the so-called quantifier words. Representing different degrees of the concentration of quantity, quantifier words in natural languages are positioned in a strict sequence – the quantifying scale. In terms of logic, it starts with nothingness (quantifier of meaningful nothingness), terminating at universality while in terms of language quantifier words, it is represented by the complex scale of quantifying words’ intensity. Logically speaking, this scale should start with the quantifier word ‘nothing’ to move all the way through increasing intensity ov

Lowpass spatial filters are adopted to match the noise statistics of the degradation seeking
good quality smoothed images. This study imply different size and shape of smoothing
windows. The study shows that using a window square frame shape gives good quality
smoothing and at the same time preserving a certain level of high frequency components in
comparsion with standard smoothing filters.

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles