The aim of this study is to establish a hybrid model for epileptic seizure detection with genetic algorithm (GA) and particle swarm optimization (PSO) to determine the optimum parameters of support vector machines (SVMs) for classification of EEG data. SVMs are one of the robust machine learning techniques and have been extensively used in many application areas. The kernel parameter’s setting for SVMs in training process effects the classification accuracy. We used GA- and PSO-based approach to optimize the SVM parameters. Compared to the GA algorithm, the PSO-based approach significantly improves the classification accuracy. It is shown that the proposed Hybrid SVM can reach a classification accuracy of up to 99.38% for the EEG datasets. Hence, the proposed Hybrid SVM is an efficient tool for neuroscientists to detect epileptic seizure in EEG.

Epileptic seizure detection using hybrid machine learning methods

EDCircles: A real-time circle detector with a false detection control

Pairwise constraints based multiview features fusion for scene classification

Effect of work material hardness and cutting parameters on performance of coated carbide tool when turning hardened steel: An optimization approach

Modified color motif co-occurrence matrix for image indexing and retrieval

A robust digital watermarking scheme for video copyright protection in the wavelet domain

A simple and precise real-time four point single sinusoid signals instantaneous frequency estimation method for portable DSP based instrumentation

The development of the information technology and computer networks facilitates easy duplication, manipulation, and distribution of digital data. Digital watermarking is one of the proposed solutions for effectively safeguarding the rightful ownership of digital images and video. We propose a public digital watermarking technique for video copyright protection in the discrete wavelet transform domain. The scheme uses binary images as watermarks. These are embedded in the detail wavelet coefficients of the middle wavelet subbands. The method is a combination of spread spectrum and quantization-based watermarking. Every bit of the watermark is spread over a number of wavelet coefficients with the use of a secret key by means of quantization. The selected wavelet detail coefficients from different subbands are quantized using an optimal quantization model, based on the characteristics of the human visual system (HVS). Our HVS-based scheme is compared to a non-HVS approach. The resilience of the watermarking algorithm is tested against a series of different spatial, temporal, and compression attacks. To improve the robustness of the algorithm, we use error correction codes and embed the watermark with spatial and temporal redundancy. The proposed method achieves a good perceptual quality and high resistance to a large spectrum of attacks.

Robust wavelet-based video watermarking scheme for copyright protection using the human visual system

A fast, simple and accurate time-varying frequency estimation method for single-phase electric power systems

We address the representation of binary images using mathematical morphology. One of the main image representations in binary mathematical morphology is the shape decomposition representation, useful for image compression, pattern recognition, and image interpolation. The binary Morphological shape decomposition (MSD) representation can be developed and generalized. With these generalizations, the binary MSD's role as an efficient image decomposition tool is extended. Initially the MSD representation is based on only “one-parameter” families of elements. A new branch is added by introducing a multistructuring element MSD based on the decomposition of images into “multiparameter” families of elements. The MSD representation contains redundant points. Examples are presented and illustrated by computer simulations.

Dragos Nicolae Vizireanu

Papers

A robust digital watermarking scheme for video copyright protection in the wavelet domain

A simple and precise real-time four point single sinusoid signals instantaneous frequency estimation method for portable DSP based instrumentation

Robust wavelet-based video watermarking scheme for copyright protection using the human visual system

A fast, simple and accurate time-varying frequency estimation method for single-phase electric power systems

Generalizations of binary morphological shape decomposition