Reza Farrahi Moghaddam

Hossein Ziaei Nafchi, Atena Shahkolaei, Reza Farrahi Moghaddam et al.

In this work, based on the local phase information of images, an objective index, called the feature similarity index for tone-mapped images (FSITM), is proposed. To evaluate a tone mapping operator (TMO), the proposed index compares the locally weighted mean phase angle map of an original high dynamic range (HDR) to that of its associated tone-mapped image calculated using the output of the TMO method. In experiments on two standard databases, it is shown that the proposed FSITM method outperforms the state-of-the-art index, the tone mapped quality index (TMQI). In addition, a higher performance is obtained by combining the FSITM and TMQI indices. The MATLAB source code of the proposed metric(s) is available at https://www.mathworks.com/matlabcentral/fileexchange/59814.

Reza Farrahi Moghaddam, Mohamed Cheriet

The Hausdorff fractal dimension has been a fast-to-calculate method to estimate complexity of fractal shapes. In this work, a modified version of this fractal dimension is presented in order to make it more robust when applied in estimating complexity of non-fractal images. The modified Hausdorff fractal dimension stands on two features that weaken the requirement of presence of a shape and also reduce the impact of the noise possibly presented in the input image. The new algorithm has been evaluated on a set of images of different character with promising performance.

Reza Farrahi Moghaddam, Yves Lemieux, Mohamed Cheriet

In this work, the implications of new technologies, more specifically the new optical FTTH technologies, are studied both from the functional and non-functional perspectives. In particular, some direct impacts are listed in the form of abandoning non-functional technologies, such as micro-registration, which would be implicitly required for having a functioning operation before arrival the new high-bandwidth access technologies. It is shown that such abandonment of non-functional best practices, which are mainly at the management level of ICT, immediately results in additional consumption and environmental footprint, and also there is a chance that some other new innovations might be 'missed.' Therefore, unconstrained deployment of these access technologies is not aligned with a possible sustainable ICT picture, except if they are regulated. An approach to pricing the best practices, including both functional and non-functional technologies, is proposed in order to develop a regulation and policy framework for a sustainable broadband access.

Reza Farrahi Moghaddam, Mohamed Cheriet

In this work, a multiple-expert binarization framework for multispectral images is proposed. The framework is based on a constrained subspace selection limited to the spectral bands combined with state-of-the-art gray-level binarization methods. The framework uses a binarization wrapper to enhance the performance of the gray-level binarization. Nonlinear preprocessing of the individual spectral bands is used to enhance the textual information. An evolutionary optimizer is considered to obtain the optimal and some suboptimal 3-band subspaces from which an ensemble of experts is then formed. The framework is applied to a ground truth multispectral dataset with promising results. In addition, a generalization to the cross-validation approach is developed that not only evaluates generalizability of the framework, it also provides a practical instance of the selected experts that could be then applied to unseen inputs despite the small size of the given ground truth dataset.

Reza Farrahi Moghaddam, Mohamed Cheriet

In this work, a new approach to the definition of the quality of experience is presented. By considering the quality of service as a baseline, that portion of the QoE that can be inferred from the QoS is excluded, and then the rest of the QoE is approached with the notion of QoE at a Boundary (QoEaaB). With the QoEaaB as the core of the proposed approach, various potential boundaries, and their associated unseen opportunities to improve the QoE are discussed. In particular, property, contract, SLA, and content are explored in terms of their boundaries and also their associated QoEaaB. With an interest in online video delivery, management of resource sharing and isolation associated with multi-tenant operations is considered. It is concluded that the proposed QoEaaB can bring a new perspective in QoE modeling and assessment toward a more enriched approach to improving the experience based on innovation and deep connectivity among actors.

Reza Farrahi Moghaddam, Mohamed Cheriet

This is the first report on Working Paper WP-RFM-14-01. The potential and capability of sparse representations is well-known. However, their (multivariate variable) vectorial form, which is completely fine in many fields and disciplines, results in removal and filtering of important "spatial" relations that are implicitly carried by two-dimensional [or multi-dimensional] objects, such as images. In this paper, a new approach, called spiralet sparse representation, is proposed in order to develop an augmented representation and therefore a modified sparse representation and theory, which is capable to preserve the data associated to the spatial relations.

Reza Farrahi Moghaddam, Fereydoun Farrahi Moghaddam, Thomas Dandres et al.

In this work, three of many ICT-specific challenges of LCA are discussed. First, the inconsistency versus uncertainty is reviewed with regard to the meta-technological nature of ICT. As an example, the semiconductor technologies are used to highlight the complexities especially with respect to energy and water consumption. The need for specific representations and metric to separately assess products and technologies is discussed. It is highlighted that applying product-oriented approaches would result in abandoning or disfavoring of new technologies that could otherwise help toward a better world. Second, several believed-untouchable hot spots are highlighted to emphasize on their importance and footprint. The list includes, but not limited to, i) User Computer-Interfaces (UCIs), especially screens and displays, ii) Network-Computer Interlaces (NCIs), such as electronic and optical ports, and iii) electricity power interfaces. In addition, considering cross-regional social and economic impacts, and also taking into account the marketing nature of the need for many ICT's product and services in both forms of hardware and software, the complexity of End of Life (EoL) stage of ICT products, technologies, and services is explored. Finally, the impact of smart management and intelligence, and in general software, in ICT solutions and products is highlighted. In particular, it is observed that, even using the same technology, the significance of software could be highly variable depending on the level of intelligence and awareness deployed. With examples from an interconnected network of data centers managed using Dynamic Voltage and Frequency Scaling (DVFS) technology and smart cooling systems, it is shown that the unadjusted assessments could be highly uncertain, and even inconsistent, in calculating the management component's significance on the ICT impacts.

Reza Farrahi Moghaddam, Shaohua Chen, Rachid Hedjam et al.

A novel method to convert color/multi-spectral images to gray-level images is introduced to increase the performance of document binarization methods. The method uses the distribution of the pixel data of the input document image in a color space to find a transformation, called the dual transform, which balances the amount of information on all color channels. Furthermore, in order to reduce the intensity variations on the gray output, a color reduction preprocessing step is applied. Then, a channel is selected as the gray value representation of the document image based on the homogeneity criterion on the text regions. In this way, the proposed method can provide a luminance-independent contrast enhancement. The performance of the method is evaluated against various images from two databases, the ICDAR'03 Robust Reading, the KAIST and the DIBCO'09 datasets, subjectively and objectively with promising results. The ground truth images for the images from the ICDAR'03 Robust Reading dataset have been created manually by the authors.

Reza Farrahi Moghaddam, Fereydoun Farrahi Moghaddam, Mohamed Cheriet

In recent years, a large number of binarization methods have been developed, with varying performance generalization and strength against different benchmarks. In this work, to leverage on these methods, an ensemble of experts (EoE) framework is introduced, to efficiently combine the outputs of various methods. The proposed framework offers a new selection process of the binarization methods, which are actually the experts in the ensemble, by introducing three concepts: confidentness, endorsement and schools of experts. The framework, which is highly objective, is built based on two general principles: (i) consolidation of saturated opinions and (ii) identification of schools of experts. After building the endorsement graph of the ensemble for an input document image based on the confidentness of the experts, the saturated opinions are consolidated, and then the schools of experts are identified by thresholding the consolidated endorsement graph. A variation of the framework, in which no selection is made, is also introduced that combines the outputs of all experts using endorsement-dependent weights. The EoE framework is evaluated on the set of participating methods in the H-DIBCO'12 contest and also on an ensemble generated from various instances of grid-based Sauvola method with promising performance.

Fereydoun Farrahi Moghaddam, Reza Farrahi Moghaddam, Mohamed Cheriet

Designing a fast and efficient optimization method with local optima avoidance capability on a variety of optimization problems is still an open problem for many researchers. In this work, the concept of a new global optimization method with an open implementation area is introduced as a Curved Space Optimization (CSO) method, which is a simple probabilistic optimization method enhanced by concepts of general relativity theory. To address global optimization challenges such as performance and convergence, this new method is designed based on transformation of a random search space into a new search space based on concepts of space-time curvature in general relativity theory. In order to evaluate the performance of our proposed method, an implementation of CSO is deployed and its results are compared on benchmark functions with state-of-the art optimization methods. The results show that the performance of CSO is promising on unimodal and multimodal benchmark functions with different search space dimension sizes.