In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that

Steganography is the art of secret communication. Its purpose is to hide the presence of information, using, for example, images as covers. The frequency domain is well suited for embedding in image, since hiding in this frequency domain coefficients is robust to many attacks. This paper proposed hiding a secret image of size equal to quarter of the cover one. Set Partitioning in Hierarchal Trees (SPIHT) codec is used to code the secret image to achieve security. The proposed method applies Discrete Multiwavelet Transform (DMWT) for cover image. The coded bit stream of the secret image is embedded in the high frequency subbands of the transformed cover one. A scaling factors ? and ? in frequency domain control the quality of the stego

In this paper, an efficient image segmentation scheme is proposed of boundary based & geometric region features as an alternative way of utilizing statistical base only. The test results vary according to partitioning control parameters values and image details or characteristics, with preserving the segmented image edges.

LK Abood, RA Ali, M Maliki, International Journal of Science and Research, 2015 - Cited by 2

Background: Obesity tends to appear in modern societies and constitutes a significant public health problem with an increased risk of cardiovascular diseases.

Objective: This study aims to determine the agreement between actual and perceived body image in the general population.

Methods: A descriptive cross-sectional study design was conducted with a sample size of 300. The data were collected from eight major populated areas of Northern district of Karachi Sindh with a period of six months (10^th January 2020 to 21^st June 2020). The Figure rating questionnaire scale (FRS) was applied to collect the demographic data and perception about body weight. Body mass index (BMI) used for ass

In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c

Embedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th