Narrow Results

Experimental results of homodyne terahertz interferometric 1-D and 2-D imaging are presented. The reconstructed images of a point source are in a good agreement with theoretical predictions. The performance of an N element detector array is imitated by only one detector placed at N positions. Continuous waves at 0.25-0.3 THz are used to detect a metal object behind a barrier. 1-D images of a C-4 sample have been obtained at several terahertz frequencies. Focusing issues of 2-D imaging have been demonstrated. The terahertz interferometric imaging method can be used in defense and security applications to detect concealed weapons, explosives as well as chemical and biological agents.

An entire industry has been developed around keyword optimization for buyers of advertising space. However, the social media landscape has shifted to photo-driven behaviors, and there is a need to overcome the challenge of analyzing the large amount of visual data that users post on the internet. We will address this analysis by providing a review on how to measure image and video interestingness and memorability from content that is tacked in real time on social networks. We will investigate state-of-the-art methods that are used to analyze social media images and present experiments that were performed to obtain comparable results based on the studied proposals and to determine which are the best characteristics and classifiers. Finally, we will discuss future research directions that could be beneficial to both users and companies.

In order to enhance the sense of reality haptic display based on image, it is widely expected to express various characteristics of the objects in the image using different kinds of haptic feedback. To this end, a multi-mode haptic display method of image was proposed in this paper, including the multi-feature extraction of image and the image expression with various types of haptic rendering. First, the device structure integrating force and vibrotactile feedbacks was designed for multi-mode haptic display. Meanwhile, the three-dimensional geometric shape, detail texture and outline of the object in the image were extracted by various image processing algorithms. Then, a rendering method for the object in the image was proposed based on the psychophysical experiments on the piezoelectric ceramic actuator. The 3D geometric shape, detail texture and outline of the object were rendered by force and vibration tactile feedbacks, respectively. Finally, these three features of the image were haptic expressed simultaneously by the integrated device. Haptic perception experiment results show that the multi-mode haptic display method can effectively improve the authenticity of haptic perception.

Aiming at the poor convergence of the current sketch image classification and unable to meet the growing network needs, a classification and model method of convolution feature in sketch image based on deep learning is proposed. Based on the classification principle of deep learning, a classification experiment was carried out on the semantic features of sketch works through the analysis of convolution neural network, convolution feature model, convolution and sketch extraction boundary. The experimental results show that the proposed convolution classification and recognition method is better than the traditional classification method and has higher accuracy in dimensionality reduction and error rate detection than the traditional method. It can better meet the needs of network intelligent processing of sketch image feature classification.

In this work the performance and computer time requirements of 15 classifiers are compared in images modeled by two-dimensional Gaussian Markov random fields which are represented by a causal autoregressive model of the second order. The per-pixel classifier and the object classifier directly or indirectly utilizing spectral-spatial characteristies of images are among them. The probability of misclassification (PMC) calculated analytically and experimentally on modeled data was used as a measure of a classifier performance. The influence of such factors as the object size and form, the inadequacy of a classifier and data models, the accuracy of spatial correlation estimation on the PMC is investigated.

The following main results are obtained. The performance of object classifiers is much better than that of per-pixel classifiers. The PMC of object classifiers decreases rapidly with the increase of the size of an object. The performance of object classifiers indirectly incorporating spatial characteristics of an object (OCIND) and that of object classifiers directly incorporating spatial characteristics (OCDIR) is similar for the linear decision rule. The performance of OCDIR is much better than that of OCIND for the quadratic decision rule. Computationally, averaging object classifiers are fastest, next are OCIND and finally OCDIR. The cross-shaped object classifier is better and faster than the square-shaped object classifier for the same number of pixels.

In this paper, we propose a simple, but efficient method to recognize two-dimensional shapes without regard to their translation, rotation, and scaling factors. In our scheme, we use all of the boundary points to calculate the first principal component, which is the first shape feature. Next, by dividing the boundary points into groups by projecting them onto the first principal component, each shape is partitioned into several blocks. These blocks are processed separately to produce the remaining shape features. In shape matching, we compare two shapes by calculating the difference between the two sets of features to see whether the two shapes are similar or not.

The amount of storage used to represent a shape in our method is fixed, unlike most other shape recognition schemes. The time complexity of our shape matching algorithm is also O(n), where n is the number of blocks. Therefore, the matching algorithm takes little computation time, and is independent of translation, rotation, and scaling of shapes.

Mobile communication has a great potential to the users due to fulfilling the dreams of real-time multimedia communication like voice, image, and text. The huge amount of data redundancy in still image should be compressed using exact image compression algorithm (ICA) before transmitting via wireless channel. Thus, an ICA should be adaptive, simple, and cost-effective and suitable for feasible implementation. Hardware implementation of the different algorithms has improved using modern, fast, and cost-effective technologies. The main aim of this paper is to review and demonstrate various ICAs developed based on image transmission via wireless channel as well as their hardware implementation. Finally, this review makes bridge for researchers to the future relative studies between different algorithms and architectures, and stands as a reference point for developing more controlling and flexible structures.

Recently a chaotic cryptographic scheme based on composition maps was proposed. This paper studies the security of the scheme and reports the following problems: (1) the scheme can be broken by a differential attack with 6 + ⌈log_L(MN)⌉ chosen plaintexts, where MN is the size of the plaintext and L is the number of different elements in plaintext; (2)the two composition maps both do not work as a secure and efficient source of random numbers; (3)the scheme is not sensitive to the changes of the plaintext.

Recently, a chaos-based image encryption algorithm called MCKBA (Modified Chaotic-Key Based Algorithm) was proposed. This paper analyzes the security of MCKBA and finds that it can be broken with a differential attack, which requires only four chosen plain-images. Performance of the attack is verified by experimental results. In addition, some defects of MCKBA, including insensitivity with respect to changes of plain-image/secret key, are reported.

In this paper, a new 4D chaos system is introduced based on the mathematical structure through composing and transferring. The behavior of the proposed chaotic system is studied using different tests, such as Lyapunov exponent, bifurcation diagram and histogram. In order to show the advantage of the new chaos system, the proposed system is used for image encryption. In the proposed algorithm, in addition to the new chaos system, cellular automata is also used to improve the security of the algorithm. The proposed algorithm has a separate structure for encryption key, which increases the security of the proposed algorithm. The security of the proposed environment which is evaluated using different types of security tests shows the efficiency of the proposed algorithm.

A combination of three algorithms is proposed that gives a reasonable rate of success in image similarity searches. All use region based statistical measures using a combination of color features, linear features, and intensities combined with a collection of methods for subdividing the image into regions. All possible combinations were evaluated and the best (highest success rate) was selected to be used as a practical image similarity measure. Component algorithms are combined using a simple decision fusion voting scheme, giving success rates in the range of 50–60%. For a web search application this is quite reasonable.

Orthogonal Matching Pursuit (OMP) is an effective solution to sparse approximation based on redundant dictionary, but there are plenty of matrix-vector multiplications in order to seek for the most matching atom. This full search scheme can consume much CPU time, especially for high dimension data such as image. Although some existing schemes proposed some accelerating methods by exploiting the property of atoms in parametric dictionary, they cannot be extended to other dictionaries, especially learned dictionary. Considering statistical nature of atoms in learned dictionary, this paper proposes a novel method which utilizes modified K-mean algorithm to cluster all the atoms in the learned dictionary while sufficiently considering the inner product operation between every two atoms, determines the class in which the desired atom locates and finally find it in the class. Some analyses and experiments have shown the success of the method. In addition, this paper gives some empirical analysis of the effect of related parameters of indexed dictionary.

Recently, on the internet, the level of image and video forgery has augmented due to the augmentation in the malware, which has facilitated user (anyone) to upload, download, or share objects online comprising audio, images, or video. Recently, Convolution Neural Network (CNN) has turn into a de-facto technique for classification of multi-dimensional data and it renders standard and also highly effectual network layer arrangements. But these architectures are limited by the speed due to massive number of calculations needed for training in addition to testing the network and also, it might render less accuracy. To trounce these issues, this paper proposed to ameliorate the image and video forgery detection’s efficiency utilizing hybrid CNN. Initially, the intensive along with incremental learning phase is carried out. After that, the hybrid CNN is implemented to detect the image together with video forgery. The developed system was tested on images together with videos for different kinds of forgeries, and it was observed that the proposed work obtains more than 98% accuracy for both testing as well as validation sets.

This paper has to be considered as a guide to solving fuzzy relational equations on the unit interval. Although the number of publications on this topic is quite impressive, there doesn't seem to exist a handy structured overview of all types of equations and their solution procedures. Our overview starts with a thorough treatment of equations and systems of equations, with a continuous triangular norm. It is shown that these are the basic problems: all other equations, image and composition equations, can be reduced to these problems. We do not only structure well-known results, we also present some new insights in the solution procedures of fuzzy relational equations.

The article is about myopia in the Asia Pacific region.

German biotech innovator Altona Diagnostics launches BioNexus-certified regional hub in Malaysia: ADT Biotech Sdn Bhd.

FEI launches "Explore the Unseen" image contest in partnership with National Geographic.

BIO applauds Representative Kaptur's Energy Investment Act of 2012.

Cytori to utilize Sistemic's SistemQC™ to strengthen understanding of mechanisms & support design of Next-Generation Cell Therapies.

Bosch packaging technology and Sartorius Stedim Biotech introduce PreVAS.

CellCentric and ZoBio enter into partnership to develop lead compounds against epigenetic drug targets.

The professional painting industry has experienced a dramatic breakthrough with the rapid expansion of computer science and technology. In the current digital era, digital painting art is extending the more significant creative space to add new content. Digital painting is the modern trend of mainstream painting presented to the public as a new generation of visual art. Creativity may show up, and new techniques of creating art can arise infinitely with the assistance of computer intelligence technology. This article explains how computer image processing is used in the production of art. The report offers a painting technique based on Image Rendering (IR), which does not rely on human expertise in the past, and a color image is turned into a photo with a painting effect automated. Image-based rendering is a novel way in which computer graphics and picture processing are drawn and combined with the requirement to build geometric models, get information from the input image simply by interpolating views, deforming images, and reconstructing the desired action. This article proposes the indirect use of picture processing technology and computer technology to produce oil painting. It will investigate the application of contemporary digital picture technology in order not only to maintain traditional tastes, and to keep pace with the pace of the times, to create traditional optimization.

The documentary patrimony deposited in the libraries and archives represents an essential part in the collective memory; it reflects the diversity of languages, peoples and cultures. But such memory is fragile and a part of such patrimony regularly disappears by accident, war or ageing.

There exist about three million manuscripts of an Arab or Islamic origin, scattered throughout the world. They are not well preserved, that is why researchers encounter difficulty in consulting them. The digitization of such documents has become an absolute necessity for saving and preserving them for future generations.

This paper presents a contribution in the domain of digitization and processing of images of historical documents stored in the Arabic libraries. After being scanned, the raw images obtained undergo a primary pre-processing treatment in order to clean them and restore them; then they go through a second phase of image analysis which consists in segmenting the documents so as to separate out texts and graphics, and in compressing the images so as to reduce their stocking cost and their communication time. All such operations are necessary for the retro conversion of the images of historical documents for the purpose of indexing and hosting them on the internet.

Wavelet Shrinkage using DWT has been widely used in de-noising although DWT has a translation variance problem. In this study, we solve this problem by using the translation invariant DWT. For this purpose, we propose a new complex wavelet, the Real-Imaginary Spline Wavelet (RI-Spline wavelet). We also propose the Coherent Dual-Tree algorithm for the RI-Spline wavelet and extend it to the 2-Dimensional. Then we apply this translation invariant RI-Spline wavelet for translation invariant de-noising. Experimental results show that our method, when applied to ECG data, the medical image and the textile surface inspection can obtain better de-noising results than that of conventional Wavelet Shrinkage.

Although there is common consensus that loyalty is an essential dynamic element in the competitive edge of certain enterprises, tourism destination loyalty has not been explored. This chapter concentrates on developing a greater understanding of the potential factors that have an impact on tourism destination loyalty. It is important to explore the importance of loyalty dimensions based on the previous theories to measure tourists’ loyalty. The hypothesis shows destination loyalty is attributed to various factors such as destination image, destination quality, destination value, and attribute satisfaction.