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This paper deals with classification algorithms as one of the basic principles of pattern recognition. We analyze their effect to a feature space and compare the type and the shape of the separating and decision surface, respectively. We proposed a novel classification approach based on Cumulative Fuzzy Membership Function that creates a decision surface in a different way as an MF ARTMAP neural network...
There are many modulation formats (such as FSK, PSK, ASK) in the process of underwater acoustic communication, and the task of the signal modulation identification is to distinguish the format that used from signals which received from acoustic communication. This technique for communication management, such as underwater acoustic communication spectrum monitoring, interference listening and signal...
Many areas include public transportation, hospitals and shopping mall use the computer technologies for security reasons. The need for integrating the technology with human needs is increased dramatically. Car license plate recognition is one of those technologies that help people to secure themselves from different attacks either attacks that affect their lives or their properties. There is an increasing...
An image-driven, model-free approach to design control systems for a large class of industrial process is proposed. A mathematical model of the process is replaced by sequences of subsequent images which play the role of the process (plant) states. The length of this sequences depends on the speed of the process dynamics and on the frame rate. Firstly, a learning sequence of the system states is collected...
This paper proposes an effective fusion scheme for extracting more discriminative information from bimodal biometrics at data, feature and decision levels. In all these three levels of fusion, information from both face andfingerprint image of a single subject are fused to effectively represent it in a more discriminative ways. For all these three approaches, a combination of wavelet and principal...
In this paper, a method of aerial handwritten Japanese katakana character recognition using the triaxial accelerometer is described. The proposed character recognition method is based on k-nearest neighbor (k-NN) algorithm using feature vectors extracted with simple signal processing. From the experiments using dataset for 46 katakana characters from specific perticipant, average recognition rate...
Over the past few years, the dimensionality of functional MRI (fMRI) effects the analysis of brain data. In the field of machine learning and statistical analysis, classification of objects plays a significant role. Machine learning classifiers are used to discover the class of new data points from a set of data points. The application of learning techniques on fMRI data alleviates to cognitive state...
This article describes a completely new, fully automatic line detector algorithm that takes advantage of look-up tables to recognize and fit straight line patterns. The algorithm first recognizes any possible 4×4 pixel line patterns among the binary edge pixels and then uses several small look up tables to decide whether the connected patterns form a line or not. It is designed for real time processing...
This work aims to present a system for automatic music mood classification based on acoustic and visual features extracted from the music. The visual features are obtained from spectrograms and the acoustic features are extracted directly from the audio signal. The texture operators used are Local Phase Quantization (LPQ), Local Binary Pattern (LBP) and Robust Local Binary Pattern (RLBP). The acoustic...
One of the challenges of the hand rehabilitation device is to create a smooth interaction between the device and user. The smooth interaction can be achieved by considering myoelectric signal generated by human's muscle. Therefore, the so-called myoelectric control system (MCS) has been developed since the 1940s. Various MCS's has been proposed, developed, tested, and implemented in various hand rehabilitation...
In this paper, a solution for an automated healthcare assessment process is proposed. Non-invasive, ambient sensors are retrieving data from patients being in their home care treatment setups. The type of sensors is limited to the tracking of inertia, motion, and alcohol gas. Low-cost sensor prototypes are developed. They constantly measure the movement and the air around the patients. The Big Data...
Grey Level Co-Occurrence matrix is one of the oldest techniques used for texture analysis. The Grey Level Co-Occurrence matrix has two important parameters i.e. distance and direction. In this paper various combinations of distance and directional angles used for GLCM calculation are analyzed in order to recognize certain patterned images based on their textural features. Patterns considered in this...
Saliency detection in images attracts much research attention for its usage in numerous multimedia applications. In this paper, we propose a saliency detection method based on optimization for RGBD images. With RGBD images, our method utilizes the depth channel to enhance the identification of background and foreground regions. We firstly generate new depth image by using non-linear transformation...
This paper presents a methodology for controlling the direction of motor taking a video sample from a camera as input. To control the direction the subject has to move his head in a direction which he would want the motor to rotate. The main challenge would be classifying the test sequence which has the data of the activity performed by the subject The actions are recognized in the frontal view by...
Myoelectric control is using electromyography (EMG) signal as a source of control, with this technique, we can control any computer based system such as robots, devices or even virtual objects. The tendon gliding exercise is one of the most common hand's rehabilitation exercises. In this paper, we present a patterns recognition based myoelectric control system (MCS) for the automatic assistance in...
Patten recognition techniques are widely used for image processing in medical imaging. It provides assistance to physicians and scientists in large scale diagnosis. In this paper, we have proposed an automated system for detecting melanoma from dermoscopic images. We detected melanoma by extracting information from region of interest (ROI) rather than the whole image composed of lesion and background...
We develop a unified framework for complex event retrieval, recognition and recounting. The framework is based on a compact video representation that exploits the temporal correlations in image features. Our feature alignment procedure identifies and removes the feature redundancies across frames and outputs an intermediate tensor representation we call video imprint. The video imprint is then fed...
We introduce Spatio-Temporal Vector of Locally Max Pooled Features (ST-VLMPF), a super vector-based encoding method specifically designed for local deep features encoding. The proposed method addresses an important problem of video understanding: how to build a video representation that incorporates the CNN features over the entire video. Feature assignment is carried out at two levels, by using the...
AdaBoost is a popular ensemble method utilized in pattern recognition problems that are considered tough. Besides being a robust technique it does suffer from few limitations viz. size of training data and presence of noise in training data. In this context, we proposed a novel technique called Perspective Based Model (PBM) for ensemble creation in case of multispectral data analysis. In the present...
Palm vein recognition is developing biometric identification technology. It can be used in physical security and information security for selective control of access to a place or resource. A palm vein recognition has been gaining research interest from last few years because it use physiological intrinsic that uniqueness, stability, not easily spoofed and damaged and have live body identification...
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