Meaningful Learning for Deep Facial Emotional Features

Neural Processing Letters - Facial expression is an important aspect to recognize emotions between humans. However, this task remains difficult for machines. Several approaches have been developed...     

An image registration algorithm based on phase correlation and the classical Lucas–Kanade technique

Image registration is defined as an important process in image processing in order to align two or more images. A new image registration algorithm for translated and rotated pairs of 2D images is presented in order to achieve subpixel accuracy and spend a small fraction of computation time. To achieve the accurate rotation estimation, we propose a two-step method. The first step uses the Fourier Mellin Transform and phase correlation technique to get the large rotation, then the second one uses the Fourier Mellin Transform combined with an enhance Lucas–Kanade technique to estimate the accurate rotation. For the subpixel translation estimation, the proposed algorithm suggests an improved Hanning window as a preprocessing task to reduce the noise in images then achieves a subpixel registration in two steps. The first step uses the spatial domain approach which consists of locating the peak of the cross-correlation surface, while the second uses the frequency domain approach, based on low-frequency (aliasing-free part) of aliased images. Experimental results presented in this work show that the proposed algorithm reduces the computational complexities with a better accuracy compared to other subpixel registration algorithms.     

Motion estimation using the fast and adaptive bidimensional empirical mode decomposition

Motion estimation is a basic step that can be used to serve several processes in computer vision. This motion is currently approximated by the visual displacement field called optical flow. Currently, several methods are used to estimate it, but a good compromise between computational cost and accuracy is hard to achieve. This paper tackles the problem by proposing a new technique based on the FABEMD (fast and adaptive bidimensional empirical mode decomposition) with the aim of improving the well-known pyramidal algorithm of Lucas and Kanade (LK) which, in principle, utilizes two consecutive frames extracted from video sequence to determine a dense optical flow. The proposed algorithm uses the FABEMD method to decompose each of the two considered frames into several BIMFs (bidimensional intrinsic mode functions) that are matched in number and proprieties. Thus, to compute the optical flow, the LK algorithm is applied to each of the two matching BIMFs which belong to the same mode of the decomposition. Although the implementation does not use an iterative refinement, the results show that the proposed approach is less sensitive to noise and provides improved motion estimation with a reduction of computing time compared to iterative methods.     

Diabetic retinopathy prediction based on deep learning and deformable registration

Multimedia Tools and Applications - Diabetic retinopathy is one of the most dangerous complications of diabetes. It affects the eyes causing damage to the blood vessels of the retina. Eventually,...     

Robust point matching via corresponding circles

Multimedia Tools and Applications - The matching points extracted from images play a very important role in many applications and particularly in computer vision. The use of point sets as being...     

A comparison of three amperometric phenoloxidase–Sonogel–Carbon based biosensors for determination of polyphenols in beers

Three phenoloxidases based biosensors were successfully developed using as electrochemical transducer a new type of electrode recently developed by our group: the “Sonogel–Carbon electrode”. The employed enzymes were Trametes versicolor laccase (Lac), Mushroom tyrosinase (Tyr), and Horseradish peroxidase (HRP). Immobilization step was accomplished by doping the electrode surface with a mixture of the individual enzyme and Nafion ion exchanger as additive-protective. The biosensor responses, optimized in beer real samples, were evaluated for five individual polyphenols. It was found that the developed biosensors were sensitive to nanomolar concentrations of the tested polyphenols. As example, the limit of detection, sensitivity, and response linear range for caffeic acid for Nafion-Lac/Sonogel–Carbon biosensor were 0.06 μmol L⁻¹, 99.6 nA μmol⁻¹ L, and 0.04–2 μmol L⁻¹, respectively. The stability and reproducibility of the biosensors were evaluated by applying them directly to beer real samples. It has been demonstrated that the Nafion-Lac/Sonogel–Carbon system is the more stable with a relative standard deviation of 3.3% (n = 10), maintaining 84% of its stable response for at least three weeks. Estimation of polyphenol index in eight lager beers and a comparison of the results with those obtained by a classical method was carried out.     

A novel discrete bat algorithm for solving the travelling salesman problem

The travelling salesman problem (TSP) is one of the well-known NP-hard combinatorial optimization and extensively studied problems in discrete optimization. The bat algorithm is a new nature-inspired metaheuristic optimization algorithm introduced by Yang in 2010, especially based on echolocation behavior of microbats when searching their prey. Firstly, this algorithm is used to solve various continuous optimization problems. In this paper we extend a discrete bat-inspired algorithm to solve the famous TSP. Although many algorithms have been used to solve TSP, the main objective of this research is to investigate this discrete version to achieve significant improvements, not only compared to traditional algorithms but also to another metaheuristics. Moreover, this study is based on a benchmark dataset of symmetric TSP from TSPLIB library.