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To extract hand tracks and hand shape features from continuous sign language videos for gesture classification using backpropagation neural network. Horn Schunck optical flow (HSOF) extracts tracking features and Active Contours (AC) extract shape features. A feature matrix characterizes the signs in continuous sign videos. A neural network object with backpropagation training algorithm classifies...
This paper presents a novel approach for hand gesture recognition based on wavelet enhanced image preprocessing and supervised Artificial Neural Networks (ANNs). Six different hand gestures are tested. The image preprocessing handles the hand gesture contour segmentation. This research includes three contributions: (1) it provides two dimensional hand gesture contour images to one dimensional signal...
Swarm operation in Unmanned Aerial Vehicles is an emerging technology which has numerous uses. It can be used in industrial, agricultural, and even military applications. However, it must be able to perform formations for it to be effective. Also, countermeasures must be made by the swarm to account for certain obstructions that are present in the environment. This paper aims to address this issue...
This paper presents an accurate and automatic algorithm to recognize and count fish in the video footages of fishery operations. The unique character of the approach is that it combines machine learning techniques with statistical methods to fully make use the benefits of these algorithms. The approach consists of three major stages including video data preparation such as noise deduction, preliminary...
Objects that have been buried underground cannot be recognized due to the opaqueness of the soil. To recognize objects that have been buried, ground penetrating radar (GPR) by the assistance of computer-aided system was used. This paper proposes the latter, which is called the Recognition System of Underground Object Shape using GPR datagram. The hyperbola from cylinder and cube metal object that...
Today shopping markets pay attention towards customer needs and services. Unfortunately the blind and vision impaired person are still incapable to access these environments without reliance. Assistive technology is trying to sway the living style of the blind by introducing support systems for routinely actions like reading, writing, walking, Web surfing, and shopping. However, still the blind have...
Load profiles are a crucial tool for power system planning and operation, and also in several operations of electricity markets. This article proposes a new methodology for the determination of load profiles based on a two-step approach. The first phase employs a neural network autoencoder to reduce the dimensionality of the input vectors. The second phase is a clustering process based on the Kohonen...
Neuromorphic computing attempts to emulate the remarkable efficiency of the human brain in vision, perception and cognition related tasks. Nanoscale devices that offer a direct mapping to the underlying neural computations have emerged as a promising candidate for such neuromorphic architectures. In this paper, a Magnetic Tunneling Junction (MTJ) has been proposed to perform the thresholding operation...
In this paper, Neumann's integral is evaluated for computing self-inductance using a multi-turn sectional matrix method. Analytical equations are derived considering the increase in dimensions of the coil due to an impinging air-gap between the turns. The resulting sectional self-inductance matrix is computed and the concepts of sectional partial self-inductance and sectional partial mutual inductance...
In the present paper a circular loop antenna based on Koch fractal geometry is designed for the multiband frequency response in the frequency range of 2–45 GHz. This band is well known for the many wireless communication band, satellite communication and microwave communication. A CAD tool based on artificial neural network (ANN) is developed for the analysis and synthesis of Koch loop fractal antenna...
Sparse representation-based classification (SRC) has been recently attracted a great interest among the signal processing society. SRC applies a discriminative representation using training samples to separate signals into their classes. In existing SRC methods, the dictionary size, which highly affects the performance, is manually set. Moreover, they are linear classifiers, and thus, they are not...
This paper introduces a flip aware patch matching frame-work that facilitates scalable sketch recognition. An overlapping spatial grid is utilized to generate an ensemble of patches for each sketch. We rank similarities between freely drawn sketches via a spatial voting process where similar patches in terms of shape and structure arbitrate for the result. Patch similarity is efficiently estimated...
Sign language recognition (SLR) is considered a multidisciplinary research area engulfing image processing, pattern recognition and artificial intelligence. The major hurdle for a SLR is the occlusions of one hand on another. This results in poor segmentations and hence the feature vector generated result in erroneous classifications of signs resulting in deprived recognition rate. To overcome this...
Deep architectures have been used in transfer learning applications, with the aim of improving the performance of networks designed for a given problem by reusing knowledge from another problem. In this work we addressed the transfer of knowledge between deep networks used as classifiers of digit and shape images, considering cases where only the set of class labels, or only the data distribution,...
Gender recognition has important applications in apparel design, social security, and human-computer interaction systems. In this paper, we investigate gender-recognition technologies using 3-D human body shape. The front and side silhouettes from 459 female subjects and 107 male subjects were extracted and then modeled using normalized Elliptic Fourier descriptors. Principal Component Analysis (PCA)...
The voice conversion system modifies the speaker specific features of the source speaker so that it sounds like a target speaker speech. The voice individuality of the speech signal is characterized at various levels such as shape of the glottal excitation, shape of the vocal tract and the long term prosodic features. In this work, Line Spectral Frequencies (LSF) are used to represent the shape of...
A new approach to recover 3-D shape from a Scanning Electron Microscope (SEM) image is described. With an ideal SEM image, 3-D shape can be recovered using the Fast Marching Method (FMM) applied to the Eikonal equation. However, when the light source direction is oblique, the correct shape cannot be obtained by the usual one-pass FMM. The new approach modifies the intensities in the original SEM image...
The brittleness of ceramic materials causes surface defect of ceramic products in the phase of manufacturing and processing. The defect on surface and subsurface will obviously decrease the fatigue life of ceramics. To improve the quality of end products, we have studied the mechanism of formation and expansion of surface defects in this paper. An improved image processing and recognition algorithm...
This paper introduces a fast Traffic Sign Recognition system developed for a robot, participant in the Autonomous Driving Competition in the Portuguese Festival of Robotics. The Autonomous Driving Robot performs detection and classification of traffic signs and traffic lights based on the analysis of images acquired by a camera mounted on its chassis. The proposed algorithm is composed of three processing...
This paper presents a comparative study of several classification methods for the task of recognizing traffic signs in urban areas. These classification methods are artificial neural network (ANN), k-nearest neighbors (kNN), support vector machine (SVM), and random forest (RF). First, HSI-based color segmentation process is applied to obtain candidate regions. Using centroid-based feature, these regions...
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