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A star image fusion method based on coordinate transformation is presented for a multi-FOV star sensor. By using coordinate transformation, simulated star images are generated and images from different FOVs are fused in the same coordinate system. Star image fusion is combined with triangle algorithm which is widely applied, and the star recognition method is improved for multi-FOV star sensor. The...
The electromyography (EMG) signals detected when muscle activates can reflect the muscle activation level and has a capability of representing human motions. In this paper, three different upper limb motion recognition methods using features extracted from EMG signals were compared to study their properties under our special circumstance. The three recognition methods are wavelet transform packet...
Surface electromyography (sEMG) is extensively investigated in human-computer interface (HCI) for prostheses control to improve the the life quality of the amputees. Near-infrared spectroscopy (NIRS) reflecting muscle activity in hemo-dynamics and metabolism, is less explored in HCI applications. Reasonably combining the advantages of both sEMG and NIRS would provide a novel approach to enhance the...
Classifier fusion methods are usually used to combine multiple classification decisions and generate better classification results than any single classifier. In order to improve object classification accuracy, it is a common method to assign weights to classifiers based on their importance in a multiple decision system. In this paper we put forward a method to weight different classifiers in classifier...
Feature extraction is a crucial part of computer vision. In this paper, we present a novel method that can automatically extract relevant features from video for action recognition and identity of human who makes the action, in single framework. We propose a watermark embedding in a video to represent a human identity as a 2-D wavelet transform. The feature extraction consists of a Deep Belief Network...
In this study we evaluated the effect of subject-related variables, i.e. hand dominance, gender and experience in using, on the performances of an EMG-based system for virtual upper limb and prosthesis control. The proposed system consists in a low density EMG sensors arrangement, a purpose-built signal-conditioning electronic circuitry and a software able to classify the gestures and to replicate...
For a fast and flexible access to the rock classification technology based on features extracted from rocks images, we propose a combination method to classify the rock type automatically with the images of core thin sections. The elements of feature space are from color and morphology features of rock images, and constructed with the statistical analysis result of standard arithmetic value into different...
The Hierarchical Graph Neuron (HGN) has already been known that, it implements a single-cycle memorization and recall operation. The scheme also utilizes small response time that is insensitive to the increases in the number of stored patterns. In this improved approach, the architecture of multidimensional HGN (mHGN) is developed so, that it is not only suitable for scrutinizing 1D- or 2D-patterns;...
A new method of star catalog optimization for multi-FOV star sensor is presented. Compared with single-FOV star sensor, multi-FOV star sensor has higher attitude accuracy and update frequency. By conducting Monte Carlo Simulation and labelling stars based on magnitude, the optimization of guide star catalog reduces the size of the catalog and improves the uniformity of the catalog, which is more suitable...
Tor is a popular anonymizing network and the existing work shows that it can preserve users' privacy from website fingerprinting attacks well. However, based on our extensive analysis, we find it is the overlap of web objects in returned web pages that make the traffic features obfuscated, thus degrading the attack detection rate. In this paper, we propose a novel active website fingerprinting attack...
Computer-based medical systems play a very important role in medical applications because they can strongly support the physicians in the decision making process. The large amount of data nowadays available, although collected from high quality sources, usually contain irrelevant, redundant, or noisy information, suggesting that not all the training instances are useful for the classification task...
In the present paper we describe a recent approach of probabilistic self-organizing maps (PRSOM). The PRSOM become more and more interesting in many fields such as: pattern recognition, clustering, classification, speech recognition, data compression, medical diagnosis… The PRSOM give an estimation of the density probability function of the data, this density dependent on the parameters of the PRSOM,...
Control chart is one of the important statistical process control tools. Abnormal situations and the potential quality problems in the production process can be judged and revealed according to the state of control chart. Thus the recognition of control chart is of great importance. To improve patterns recognition performance of control chart, a new method based on improved sequential forward selection...
An improved ORB (Oriented FAST and Rotated BRIEF) algorithm motivated by SIFT (Scale-Invariant Feature Transform) is put forward aimed at solving the deficiency that ORB has little scale invariance for feature points matching. Firstly, the scale spaces were built for the detection of stable extreme points, and the stable extreme points detected were considered to be feature points with scale invariance...
A multifunctional myoelectric prosthetic hand is a perfect gift for an upper-limb amputee, however, the myoelectric control for a prosthetic hand is not so good now. Here, the paper presents a comparative study on electromyography (EMG) pattern recognition based on PCA and LDA for an anthropomorphic robotic hand. Four channels of surface EMG (sEMG) signals were recorded from the subject's forearm...
The reliance on object or people detection is rapidly growing beyond surveillance to industrial and social applications. The Histogram of Oriented Gradients (HOG), one of the most popular detection algorithms, achieves a high detection accuracy but delivers just under 1 frame-per-second (fps) on a high-end CPU. In this paper we explore the FPGA implementation of HOG using reduced bit-width fixed-point...
Sign language provides hearing and speech impaired people with an interface to communicate with society. Unfortunately most people do not understand sign language. For this, image processing and pattern recognition can provide with a vital tool to detect and translate sign language into vocal language. This work presents a method for detecting, understanding and translating sign language gestures...
The more complete the training set of an optical character recognition platform, the greater the chances of obtaining a better precision in transcription. The development of a database for such purpose is a task of paramount effort as it is performed manually and must be as extensive as possible in order to potentially cover all words in a language. Dealing with historic documents either handwritten,...
We consider the problem of detecting mitotic figures in breast cancer histology slides. We investigate whether the performance of state-of-the-art detection algorithms is comparable to the performance of humans, when they are compared under fair conditions: our test subjects were not previously exposed to the task, and were required to learn their own classification criteria solely by studying the...
In the last decade many approaches have been introduced that allow for automatic classification of brain tumors by means of pattern recognition and magnetic resonance spectroscopy. Despite promising classification accuracies, none of these methods has found its way into clinical practice, which is also related to the missing transparency for the basis of their decision making. In this work, we develop...
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