An Algorithm for Real-Time Blind Image Quality Comparison and Assessment

This research aims at providing means to image comparison from different image processing algorithms for performance assessment purposes. Reconstruction of images corrupted by blur and noise requires specialized filtering techniques. Due to the immense effect of these corruptive parameters, it is often impossible to evaluate the quality of a reconstructed image produced by one technique versus another. The algorithm presented here is capable of performing this comparison analytically and quantitatively at a low computational cost (real-time) and high efficiency. The parameters used for comparison are the degree of blurriness, information content, and the amount of various types of noise associated with the reconstructed image. Based on a heuristic analysis of these parameters the algorithm assesses the reconstructed image and quantify the quality of the image by characterizing important aspects of visual quality. Extensive effort has been set forth to obtain real-world noise and blur conditions so that the various test cases presented here could justify the validity of this approach well. The tests performed on the database of images produced valid results for the algorithms consistently. This paper presents the description and validation (along with test results) of the proposed algorithm for blind image quality assessment.DOI:http://dx.doi.org/10.11591/ijece.v2i1.112 

A Study on Enhance Security of Visual Cryptography Using Steganography

Steganography is a process that hides secrete message or secrete hologram or secrete video or secrete image whose mere presence within the source data should be undetectable and use for transmitting secret information over public media. Visual cryptography is a cryptographic technique in which no cryptographic computation is needed at the decryption end and the decryption is performed by the human visual system (HVS). In this paper, both Steganography and visual cryptography have been selected to provide more secure data transmission over the public media with less hazard of computation. This technique generates shares with less space overhead as well as without increasing the computational complexity compared to existing techniques and may provide better security. It is also easy to implement like other techniques of visual cryptography. Finally, experimental results are given to establish the security criteria

MedGAN: Medical Image Translation using GANs

Image-to-image translation is considered a new frontier in the field of medical image analysis, with numerous potential applications. However, a large portion of recent approaches offers individualized solutions based on specialized task-specific architectures or require refinement through non-end-to-end training. In this paper, we propose a new framework, named MedGAN, for medical image-to-image translation which operates on the image level in an end-to-end manner. MedGAN builds upon recent advances in the field of generative adversarial networks (GANs) by merging the adversarial framework with a new combination of non-adversarial losses. We utilize a discriminator network as a trainable feature extractor which penalizes the discrepancy between the translated medical images and the desired modalities. Moreover, style-transfer losses are utilized to match the textures and fine-structures of the desired target images to the translated images. Additionally, we present a new generator architecture, titled CasNet, which enhances the sharpness of the translated medical outputs through progressive refinement via encoder-decoder pairs. Without any application-specific modifications, we apply MedGAN on three different tasks: PET-CT translation, correction of MR motion artefacts and PET image denoising. Perceptual analysis by radiologists and quantitative evaluations illustrate that the MedGAN outperforms other existing translation approaches.Comment: 16 pages, 8 figure

Secure Authentication Using Visual Cryptography

Abstract -Visual Cryptography is a cryptographic technique which allows visual information (text, picture, etc.) to be encrypted in such a way that decryption becomes a mechanical operation that does not require a computer. Visual Cryptography deals with any type of secrets such as printed or pictures, etc. These secrets are delivered into the system in a digital (image) form. The secrets which are in a digital form divided into different parts based on the pixel of the digital secret. These parts are called shares. To visualize the secret, the shares are then overlapped correctly.This paper introduces secure authentication using Visual Cryptography. In any authentication system the major problem is the authenticity of the customer. Due to unavoidable hacking of the database on the internet, it is always difficult to trust the information on the internet. To solve this authentication problem, we are discussing with the two most important topics based on image processing and visual cryptography

Datos no estructurados no textuales: desarrollo de nuevas tecnologías

Cuando una persona recibe estímulos sensoriales de tipo visual o auditivo reacciona realizando una asociación y reconocimiento en forma natural, como consecuencia de la información que los estímulos le brindan. Durante los últimos años, el avance de los medios digitales y la proliferación de su uso ha generado la necesidad del desarrollo de herramientas que permitan la eficiente representación, procesamiento y administración (acceso y recuperación) de información de contenido multimedial. En este contexto, la información almacenada principalmente en forma de audio, imagen y video se ha convertido en la principal materia prima utilizada por los sistemas computacionales para la transmisión de información en forma rápida y eficiente, principalmente aquella relacionada con la toma de decisiones y la resolución de problemas de índole general. Dadas sus particularidades, dicha información es catalogada como información no estructurada y su administración y manipulación requiere de la definición de nuevos procesos y métodos que faciliten y agilicen el uso de la misma. Esta propuesta de trabajo establece los lineamientos a seguir con la intención de redefinir nuevas tecnologías para el procesamiento de información no estructurada que permita la incorporación de la misma en procesos generales de resolución de problemas o toma de decisiones.Eje: Computación gráfica, imágenes y visualizaciónRed de Universidades con Carreras en Informática (RedUNCI

Datos no estructurados no textuales: desarrollo de nuevas tecnologías

Cuando una persona recibe estímulos sensoriales de tipo visual o auditivo reacciona realizando una asociación y reconocimiento en forma natural, como consecuencia de la información que los estímulos le brindan. Durante los últimos años, el avance de los medios digitales y la proliferación de su uso ha generado la necesidad del desarrollo de herramientas que permitan la eficiente representación, procesamiento y administración (acceso y recuperación) de información de contenido multimedial. En este contexto, la información almacenada principalmente en forma de audio, imagen y video se ha convertido en la principal materia prima utilizada por los sistemas computacionales para la transmisión de información en forma rápida y eficiente, principalmente aquella relacionada con la toma de decisiones y la resolución de problemas de índole general. Dadas sus particularidades, dicha información es catalogada como información no estructurada y su administración y manipulación requiere de la definición de nuevos procesos y métodos que faciliten y agilicen el uso de la misma. Esta propuesta de trabajo establece los lineamientos a seguir con la intención de redefinir nuevas tecnologías para el procesamiento de información no estructurada que permita la incorporación de la misma en procesos generales de resolución de problemas o toma de decisiones.Eje: Computación gráfica, imágenes y visualizaciónRed de Universidades con Carreras en Informática (RedUNCI

Design and perceptual validation of performance measures for salient object segmentation

Empirical evaluation of salient object segmentation methods requires i) a dataset of ground truth object segmen-tations and ii) a performance measure to compare the out-put of the algorithm with the ground truth. In this paper, we provide such a dataset, and evaluate 5 distinct performance measures that have been used in the literature practically and psychophysically. Our results suggest that a measure based upon minimal contour mappings is most sensitive to shape irregularities and most consistent with human judge-ments. In fact, the contour mapping measure is as predic-tive of human judgements as human subjects are of each other. Region-based methods, and contour methods such as Hausdorff distances that do not respect the ordering of points on shape boundaries are significantly less consistent with human judgements. We also show that minimal contour mappings can be used as the correspondence paradigm for Precision-Recall analysis. Our findings can provide guid-ance in evaluating the results of segmentation algorithms in the future. 1