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In this paper, a new method is proposed to provide a reliable and accurate algorithm to search and precisely find the center of a reference image in a set of video frames. By implementing algorithms such as SIFT and PCA-SIFT, some matched points are obtained. Some of these points are accurate, some of them are not strictly accurate and others are incorrect. As a result, registration process may be...
Edge detection is an important task in image processing and becomes more complex for the colour image which provides more information in comparison to the gray image. In this paper it will be presented a colour edge detection approach based on the product of multiscale wavelet transform. The use of the product of multiscale transform improves the localization of detected edges comparing to the one...
One of the aims of brain-computer interface (BCI) is to restore the means of communication for people suffering severe motor impairment, anarthria, or persisting in a vegetative state. Yes/no decoding with the help of an imaging technology such as functional near-infrared spectroscopy (fNIRS) can make this goal a reality. fNIRS is a relatively new non-invasive optical imaging modality offering the...
In this paper we have classified two movement intensions (left and right) using mental arithmetic and mental counting for development of brain-computer interface (BCI). Mental arithmetic task was associated to left movement intension and right movement intension was acquired using mental counting. The brain signals of four healthy subjects were acquired using functional near-infrared spectroscopy...
This paper deals with the influence of global and local objective image parameters of the analyzed image on the process of finding corresponding points. We examined the impact of objective parameters on the usability of some significant point detectors. Moreover, the paper also contains the comparison of the reliability of finding corresponding points for a particular image point by using common methods...
In this paper we propose a method to add scale-invariance to line descriptors for wide baseline matching purposes. While finding point correspondences among different views is a well-studied problem, there still remain difficult cases where it performs poorly, such as textureless scenes, ambiguities and extreme transformations. For these cases using line segment correspondences is a valuable addition...
We propose a linear dimensionality reduction method, Composite Discriminant Factor (CDF) analysis, which searches for a discriminative but compact feature subspace that can be used as input to classifiers that suffer from problems such as multi-collinearity or the curse of dimensionality. The subspace selected by CDF maximizes the performance of the entire classification pipeline, and is chosen from...
Object information is an important cue to discriminate between activities that draw part of their meaning from context. Most of current work either ignores this information or relies on specific object detectors. However, such object detectors require a significant amount of training data and complicate the transfer of the action recognition framework to novel domains with different objects and object-action...
Circular array interferometer with analog phase detector requires higher signal to noise ratio than the digital phase detection structure, which leads to lower accuracy of direction-of-arrival (DOA) estimation. T o overcome this, we proposed two kinds of methods which can work together. They are the modified phase accumulation method (MPAM) and the optimal baseline pair method (OBPM). Modified phase...
We introduce, in this paper, a simplified architecture of the Minimum and Maximum Spread (MMS) estimation method, entitled the modified Minimum and Maximum Spread (mMMS) estimation method. The mMMS method aims to detect the neural spikes efficiently. Both detectors, with different buffer sizes, are designed and implemented. Through simulation, it is shown that the circuit implemented with the mMMS...
We consider the problem of failure detection in networks with energy and communication constraints. Most of current implementations of unreliable failure detectors (FD) use mechanisms to notify process failures in fully connected networks with reliable communication links. This assumption is not applicable to lossy networks. Furthermore, such implementations do not consider resource limitations in...
Although user cooperation improves sensing accuracy, a large number of secondary users (SUs) reporting decisions may cause significant overhead. In this paper, we propose a distributed scheme, called adaptive cooperative sensing (ACS), to reduce the sensing overhead while satisfying sensing accuracy requirements. In ACS, an anchor SU requires cooperative sensing only when it does not detect the presence...
Nowadays, different sensors are widely used in many industrial purposes. Many types of sensors are changing the capacitance or the inductance of a circuit when a parameter such as distance, pressure, temperature, mass, humidity and so on is changed. Any change in inductance and capacitance also leads to change the resonance frequency of the designed proposed circuit. In this paper a circuit is designed...
Quaternion technique is applied to model the polarimetric statistical MIMO radar system, where electromagnetic vector sensors are employed at each receiver to exploit polarization information of reflected signal. Based on the refined quaternion model, quaternion adaptive detector and its complex counterpart are compared and analyzed. The quaternion adaptive detector outperforms its complex counterpart...
In this paper, we present a novel automatic marker detection method for X-ray images in the framework of machine learning, which is different from those approaches using traditional template matching or fitting algorithms based on prior knowledge. First we propose to use the covariance-based descriptors to effectively represent the marker features in X-ray images. Then we utilize the cascade of LogitBoost...
We propose a multi-person tracking framework using only one single camera in this paper. We utilize particle filter as the tracking framework and train a SVM classifier by reliable examples extracted from associated detections without occlusion. Based on the results of data association, we integrate the target's velocity into weights calculation to handle object occlusion assuming that fast-moving...
In cognitive informatics, attention is drawn to create, model, analyze and interact with three-dimensional representation of the objects from the environment. Having a precise 3D scanner solution for an affordable price is an important step to achieve this goal. Our research group focuses on creating such a solution consisting of a scanner device and a software component. As part of the research,...
In this paper, we propose an improved edge detection method based on the Laplacian operator. The improved edge detector is constructed by combining the optimal criteria for zero-crossing based edge detector and the edge-matching model for Laplacian operator-based edge detector. In order to extract the edges objectively, an unsupervised thresholding technique is introduced. Finally, the validity of...
In this paper, we introduce a set of new visual representations for complex systems. These visual representations allow for the efficient description of systems that encapsulate a variety of components that can be merged together to form ensembles. These ensemble methods can outperform individual approaches. The whole operation of such systems can be better interpreted using visual tools. Thus, we...
In this paper we classify the functional near-infrared spectroscopy (fNIRS) signals corresponding to right-and left-wrist motor imagery using various temporal windows of the response data. Signals are acquired from the primary motor cortex of five healthy subjects during right- and left-wrist motor imagery tasks using a continuous wave fNIRS system. Linear discriminant analysis is used to classify...
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