A Reduced Reference Image Quality Measure Using Bessel K Forms Model for Tetrolet Coefficients

In this paper, we introduce a Reduced Reference Image Quality Assessment (RRIQA) measure based on the natural image statistic approach. A new adaptive transform called "Tetrolet" is applied to both reference and distorted images. To model the marginal distribution of tetrolet coefficients Bessel K Forms (BKF) density is proposed. Estimating the parameters of this distribution allows to summarize the reference image with a small amount of side information. Five distortion measures based on the BKF parameters of the original and processed image are used to predict quality scores. A comparison between these measures is presented showing a good consistency with human judgment

Compressing Images Using Multi-Level Wavelet Transform Algorithm (MWTA)

This study aims to use Wavelet Transform Algorithm for image compression. Multi-levels were used in this study with the aim to produce better results for compressing images.The Multi-level Wavelet Transform Algorithm (MWTA) consists of three phases namely, first level compression, second level compressing in the first level, and algorithm validation by compare.Therefore, Vaishnavi method is used to design and develop the prototype model.In this study, the experiment was conducted using different images (RGB). The algorithm and comparison was simulated using Matlab application. The results revealed that Multi-level Wavelet Transform Algorithm (MWTA) can be used in more than one level in this algorithm but the efficiency of this algorithm for compressing was found to be in the first level in terms of size

Biometric Security System for Fake Detection using image Quality Assessment Techniques

Biometric Identification is the best security system in developing security world. Hackers made a fake biometric in easy way, so it reduce the security accuracy. Biometric security system are hacked by using two types of attack, direct or spoofing attack & indirect attack. So, there is a need to develop a new and efficient protection measure. Here, three biometric techniques - face recognition, fingerprint and iris recognition (Multi-biometric system) are used to detect whether the image is real or fake. This protection method uses Image Quality Assessment (IQA) technique. If the image is a real, it checks whether the image belongs to an authorized person or not. Out of the three biometric techniques, face recognition using Discriminate Power Analysis (DPA) technique is used for detecting authorized person. The objective is to increase the security of biometric recognition framework by adding liveness assessment in fast, non-invasive & user friendly manner. This approach protects the biometric security system from direct and indirect attack. The complexity of the proposed system is very low because it extracts 31 image quality measures from one image