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Optimizing the utilization factor of the system resources such as efficiency, bandwidth, and the storage capacity for cost reduction is one important aim of enormous amount of studies. For the image compression one can use the embedded processors as the most suitable ones. This image compression schemes for images will be based on the Discrete Cosi...
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This paper presents the design and optimization of image compression and ciphering depend on optimized Embedded Zero tree of Wavelet (EZW) techniques. Nowadays, the compression and ciphering of image have become particularly important in a protected image storage and communication. The challenge is put in application for both compression and encryp...
Citations
... Capturing several images with the help of camera is done by every computer vision application [7]. Compression of images eliminate unnecessary or non-essential information from a digital image to reduce the amount of data required to depict it [1]. Many of compression techniques like JPEG and JPEG2000 are used recently [6]. ...
The purpose of this work is to design an efficient image compression system using wavelet transforms and image approximation by modifying the wavelet coefficient. The efficiency of the system will be tested using a test image and determining the Mean Square Error (MSE). 2D-daubechies wavelet transformation with global threshold for wavelet coefficients and numerical presentation utilizing Matlab programming are the techniques used. The Discrete Wavelet Transform (DWT) has a basic principle of splitting signals into two parts namely; the high frequencies and low frequencies. For a number of repetitions, the low frequency section is further divided into high and low frequency parts, which are generally chosen by the application. The performance of an image compression system is commonly measured by calculating the MSE and the Peak Signal to Noise Ratio (PSNR).
... Capturing several images with the help of camera is done by every computer vision application [7]. Compression of images eliminate unnecessary or non-essential information from a digital image to reduce the amount of data required to depict it [1]. Many of compression techniques like JPEG and JPEG2000 are used recently [6]. ...
The purpose of this work is to design an efficient image compression system using wavelet transforms and image approximation by modifying the wavelet coefficient. The efficiency of the system will be tested using a test image and determining the Mean Square Error (MSE). 2D-daubechies wavelet transformation with global threshold for wavelet coefficients and numerical presentation utilizing Matlab programming are the techniques used. The Discrete Wavelet Transform (DWT) has a basic principle of splitting signals into two parts namely; the high frequencies and low frequencies. For a number of repetitions, the low frequency section is further divided into high and low frequency parts, which are generally chosen by the application. The performance of an image compression system is commonly measured by calculating the MSE and the Peak Signal to Noise Ratio (PSNR).
... Image compression reducing the amount of data required to represent a digital image by removing redundant or non-vital data. There are different types of redundancy present in an image, such as Spatial Redundancy, Statistical Redundancy and Human Vision Redundancy [8]. ...
... Lossless compression technique involves no loss of information. If data have been lossless compressed the original data can be recovered exactly from the compressed data, Lossless compression is generally used for applications that cannot tolerate any difference between the original and reconstructed data [8]. ...
... Near lossless compression technique is a lossy compression method where the reconstructed pixels differ from the original pixels by no more than a predetermined value, in near-lossless compression data is guaranteed to be within a specified range based on the near-lossless threshold [8]. ...
... Late methodologies for Facial Emotion Detection are Template Based Method and Feature Based Method. [3] Template Based Method This methodology utilized the normal face for every classification of feeling and characterizes the individual facial expression as indicated by the best match of every layout. This methodology for feeling order from static images has just exceptionally restricted detection and speculation capacities. ...
Emotion Recognition is such a challenging yet interesting area of research which has attracted a large number of researchers from so many varying backgrounds [Computer Graphics, Artificial Intelligence, Robotics, psychology and many more].The research consists of a hybrid process which uses Principal Component Analysis [algorithm] and Knowledge Based system to detect a face emotion. The algorithm uses the PCA for transformation of the related variables into Principal Components for the face recognition and extraction of action units (i.e. eyes and lips) and it is used after segmentation and detection of connected regions.
