Describing Colors, Textures and Shapes for Content Based Image Retrieval - A Survey

Visual media has always been the most enjoyed way of communication. From the advent of television to the modern day hand held computers, we have witnessed the exponential growth of images around us. Undoubtedly it's a fact that they carry a lot of information in them which needs be utilized in an effective manner. Hence intense need has been felt to efficiently index and store large image collections for effective and on- demand retrieval. For this purpose low-level features extracted from the image contents like color, texture and shape has been used. Content based image retrieval systems employing these features has proven very successful. Image retrieval has promising applications in numerous fields and hence has motivated researchers all over the world. New and improved ways to represent visual content are being developed each day. Tremendous amount of research has been carried out in the last decade. In this paper we will present a detailed overview of some of the powerful color, texture and shape descriptors for content based image retrieval. A comparative analysis will also be carried out for providing an insight into outstanding challenges in this field

Secure Image Steganography using Cryptography and Image Transposition

Information security is one of the most challenging problems in today's technological world. In order to secure the transmission of secret data over the public network (Internet), various schemes have been presented over the last decade. Steganography combined with cryptography, can be one of the best choices for solving this problem. This paper proposes a new steganographic method based on gray-level modification for true colour images using image transposition, secret key and cryptography. Both the secret key and secret information are initially encrypted using multiple encryption algorithms (bitxor operation, bits shuffling, and stego key-based encryption); these are, subsequently, hidden in the host image pixels. In addition, the input image is transposed before data hiding. Image transposition, bits shuffling, bitxoring, stego key-based encryption, and gray-level modification introduce five different security levels to the proposed scheme, making the data recovery extremely difficult for attackers. The proposed technique is evaluated by objective analysis using various image quality assessment metrics, producing promising results in terms of imperceptibility and security. Moreover, the high quality stego images and its minimal histogram changeability, also validate the effectiveness of the proposed approach.Comment: A simple but effective image steganographic method, providing secure transmission of secret data over Internet. The final published version of the paper can be downloaded from the link: (http://www.neduet.edu.pk/NED-Journal/2015/15vol4paper3.html). Please contact me at [email protected] if you need the final formatted published version of the pape

Steganography: A Secure way for Transmission in Wireless Sensor Networks

Addressing the security concerns in wireless sensor networks (WSN) is a challenging task, which has attracted the attention of many researchers from the last few decades. Researchers have presented various schemes in WSN, addressing the problems of processing, bandwidth, load balancing, and efficient routing. However, little work has been done on security aspects of WSN. In a typical WSN network, the tiny nodes installed on different locations sense the surrounding environment, send the collected data to their neighbors, which in turn is forwarded to a sink node. The sink node aggregate the data received from different sensors and send it to the base station for further processing and necessary actions. In highly critical sensor networks such as military and law enforcement agencies networks, the transmission of such aggregated data via the public network Internet is very sensitive and vulnerable to various attacks and risks. Therefore, this paper provides a solution for addressing these security issues based on steganography, where the aggregated data can be embedded as a secret message inside an innocent-looking cover image. The stego image containing the embedded data can be then sent to fusion center using Internet. At the fusion center, the hidden data is extracted from the image, the required processing is performed and decision is taken accordingly. Experimentally, the proposed method is evaluated by objective analysis using peak signal-to-noise ratio (PSNR), mean square error (MSE), normalized cross correlation (NCC), and structural similarity index metric (SSIM), providing promising results in terms of security and image quality, thus validating its superiority

A novel magic LSB substitution method (M-LSB-SM) using multi-level encryption and achromatic component of an image

Image Steganography is a thriving research area of information security where secret data is embedded in images to hide its existence while getting the minimum possible statistical detectability. This paper proposes a novel magic least significant bit substitution method (M-LSB-SM) for RGB images. The proposed method is based on the achromatic component (I-plane) of the hue-saturation-intensity (HSI) color model and multi-level encryption (MLE) in the spatial domain. The input image is transposed and converted into an HSI color space. The I-plane is divided into four sub-images of equal size, rotating each sub-image with a different angle using a secret key. The secret information is divided into four blocks, which are then encrypted using an MLE algorithm (MLEA). Each sub-block of the message is embedded into one of the rotated sub-images based on a specific pattern using magic LSB substitution. Experimental results validate that the proposed method not only enhances the visual quality of stego images but also provides good imperceptibility and multiple security levels as compared to several existing prominent methods.Comment: This paper has been published in Multimedia Tools and Applications Journal with impact factor=1.058. The readers can study the formatted paper using the following link: http://link.springer.com/article/10.1007/s11042-015-2671-9. Please use sci-hub.org for downloading this paper if you are unable to access it freely or email us at [email protected]