Face Recognition based on Oriented Complex Wavelets and FFT

The Face is a physiological Biometric trait used in Biometric System. In this paper face recognition using oriented complex wavelets and Fast Fourier Transform (FROCF) is proposed. The five-level Dual Tree Complex Wavelet Transform (DTCWT) is applied on face images to get shift invariant and directional features along±15o,±45o and±75o angular directions. The different pose, illumination and expression variations of face images are represented in frequency domain using Fast Fourier Transform (FFT) resulting in FFT features. Features of DTCWT and FFT are fused by arithmetic addition to get final features. Euclidean Distance classifier is applied to the features to recognize the genuine and imposter faces. The Performance analysis of proposed method is tested with ORL, JAFFE, L-SPACEK and CMU-PIE having different illumination and pose conditions. The Results shows that Recognition Rate of proposed FROCF is better compared to Existing Recognition Methods

IRHDF: Iris Recognition using Hybrid Domain Features

Iris Biometric is a unique physiological noninvasive trait of human beings that remains stable over a person's life. In this paper, we propose an Iris Recognition using Hybrid Domain Features (IRHDF) as Dual Tree Complex Wavelet Transform (DTCWT) and Over Lapping Local Binary Pattern (OLBP). An eye is preprocessed to extract the complex wavelet features to obtain the Region of Interest (ROI) area from an iris. OLBP is further applied on ROI to generate features of magnitude coefficients. Resultant features are generated by fusion of DTCWT and OLBP using arithmetic addition. Euclidean Distance (ED) is used to match the test iris image with database iris features to recognize a person. We observe that the values of Equal Error Rate (EER) and Total Success Rate (TSR) are better than in [7]

An OLBP Based Transform Domain Face Recognition

The face is an efficient physiological biometric trait to authenticate a person without any cooperation. In this paper, we propose an Overlap Local Binary Pattern (OLBP) on Transform Domain based Face Recognition (OTDFR). The two sets of OLBP features are generated from transform domain. The first set of Overlap Local Binary Pattern (OLBP) features are extracted from Dual Tree Complex Wavelet Transform (DTCWT) coefficients of High frequency components of Discrete Wavelet Transforms (DWT). The second set of OLBP features are extracted from DTCWT coefficients. The final features are generated by concatenating features of set 1 and set 2. The test image features are compared with database features using Euclidian Distance (ED). It is observed that the percentage recognition rate is high in the case of proposed algorithm compared to existing algorithms

IRDO: Iris Recognition by Fusion of DTCWT and OLBP

Iris Biometric is a physiological trait of human beings. In this paper, we propose Iris an Recognition using Fusion of Dual Tree Complex Wavelet Transform (DTCWT) and Over Lapping Local Binary Pattern (OLBP) Features. An eye is preprocessed to extract the iris part and obtain the Region of Interest (ROI) area from an iris. The complex wavelet features are extracted for region from the Iris DTCWT. OLBP is further applied on ROI to generate features of magnitude coefficients. The resultant features are generated by fusing DTCWT and OLBP using arithmetic addition. The Euclidean Distance (ED) is used to compare test iris with database iris features to identify a person. It is observed that the values of Total Success Rate (TSR) and Equal Error Rate (EER) are better in the case of proposed IRDO compared to the state-of-the art technique

Methods of electroencephalographic signal analysis for detection of small hidden changes

The aim of this study was to select and evaluate methods sensitive to reveal small hidden changes in the electroencephalographic (EEG) signal. Two original methods were considered

The relationship between stimulus intensity and response amplitude for the photopic negative response of the flash electroretinogram

The aim of this study was to investigate the relationship between stimulus intensity and response amplitude for the photopic negative response (PhNR) of the flash ERG. Specific aims were (i) to determine whether a generalized Naka-Rushton function provided a good fit to the intensity-response data and (ii) to determine the variability of the parameters of the best-fitting Naka-Rushton models. Electroretinograms were recorded in 18 participants, on two occasions, using both DTL fibre and skin active electrodes, in response to Ganzfeld red stimuli (Lee filter "terry red") ranging in stimulus strength from -1.30 to 0.53 log cd.s.m(-2) (0.28-2.11 log phot td.s) presented over a steady blue background (Schott glass filter BG28; 3.9 log scot td). PhNR amplitude was measured from b-wave peak and from pre-stimulus baseline. The Naka-Rushton function was fitted to all intensity-response data, and parameters, 'n', 'Vmax' and 'K' were obtained. Coefficients of variation (CoV), and inter-ocular and inter-session limits of agreement (LoA) were calculated for both Naka-Rushton parameters. A generalized Naka-Rushton function was found to provide a good fit to the intensity-response data, except at the highest stimulus intensity, where a reduction in amplitude occurred in many individuals. The 'Vmax' parameter was less variable than 'K' for all intensity-response data. Variability was lower for DTL than skin electrodes, and for peak-to-trough PhNR measurements, compared to baseline-to-trough. This study has demonstrated for the first time that the Naka-Rushton model provides a useful means of quantifying the intensity-response relationship of the PhNR

Morphological and Functional Changes in the Retina after Chronic Oxygen-Induced Retinopathy

The mouse model of oxygen-induced retinopathy (OIR) has been widely used for studies of retinopathy of prematurity (ROP). This disorder, characterized by abnormal vascularization of the retina, tends to occur in low birth weight neonates after exposure to high supplemental oxygen. Currently, the incidence of ROP is increasing because of increased survival of these infants due to medical progress. However, little is known about changes in the chronic phase after ROP. Therefore, in this study, we examined morphological and functional changes in the retina using a chronic OIR model. Both the a- and b-waves in the OIR model recovered in a time-dependent manner at 4 weeks (w), 6 w, and 8 w, but the oscillatory potential (OP) amplitudes remained depressed following a return to normoxic conditions. Furthermore, decrease in the thicknesses of the inner plexiform layer (IPL) and inner nuclear layer (INL) at postnatal day (P) 17, 4 w, and 8 w and hyperpermeability of blood vessels were observed in conjunction with the decrease in the expression of claudin-5 and occludin at 8 w. The chronic OIR model revealed the following: (1) a decrease in OP amplitudes, (2) morphological abnormalities in the retinal cells (limited to the IPL and INL) and blood vessels, and (3) an increase in retinal vascular permeability via the impairment of the tight junction proteins. These findings suggest that the experimental animal model used in this study is suitable for elucidating the pathogenesis of ROP and may lead to the development of potential therapeutic agents for ROP treatment

Genetics, fertility behaviour and molecular marker analysis of a new TGMS line, TS6, in rice

The thermosensitive genic male sterility (TGMS) system has great potential for revolutionizing hybrid rice production through simple, less expensive and more efficient seed production technology. For the successful utilization of this novel male sterility system, knowledge of the breeding and fertility behaviour of a TGMS line is essential. In this study, the fertility transformation behaviour, the critical fertility and sterility temperatures and the mode of inheritance of male sterility were studied for a new TGMS line, TS6, identified at Tamil Nadu Agricultural University, Coimbatore, India. The pollen and spikelet fertilities recorded on plants raised at fortnightly intervals revealed that this line was completely sterile for 78 consecutive days (35/22 to 32/23�C, maximum/minimum temperatures) and reverted to fertile when the temperature was 30/18�C. It remained fertile continuously for 69 days and the maximum pollen and spikelet fertilities recorded were 75 and 70%, respectively. The fertility was highly influenced by daily maximum temperature followed by average and minimum temperatures. It was not influenced by relative humidity, sunshine hours or photoperiod. The critical temperature inducing sterility and fertility was 26.7 and 25.5�C, respectively. The male sterility in TS6 was inherited as a monogenic recessive in the F2 and BC1 populations of TS6 · MRST9 as well as TS6 · IR68281B. Using bulked segregant analysis on an F2 population of TS6 · MRST9, an RAPD marker, OPC052962, was identified to be associated with TGMS in TS6

Neural Correlates of Visual Motion Prediction

Predicting the trajectories of moving objects in our surroundings is important for many life scenarios, such as driving, walking, reaching, hunting and combat. We determined human subjects’ performance and task-related brain activity in a motion trajectory prediction task. The task required spatial and motion working memory as well as the ability to extrapolate motion information in time to predict future object locations. We showed that the neural circuits associated with motion prediction included frontal, parietal and insular cortex, as well as the thalamus and the visual cortex. Interestingly, deactivation of many of these regions seemed to be more closely related to task performance. The differential activity during motion prediction vs. direct observation was also correlated with task performance. The neural networks involved in our visual motion prediction task are significantly different from those that underlie visual motion memory and imagery. Our results set the stage for the examination of the effects of deficiencies in these networks, such as those caused by aging and mental disorders, on visual motion prediction and its consequences on mobility related daily activities

EEG Biofeedback as a Treatment for Substance Use Disorders: Review, Rating of Efficacy, and Recommendations for Further Research

Electroencephalographic (EEG) biofeedback has been employed in substance use disorder (SUD) over the last three decades. The SUD is a complex series of disorders with frequent comorbidities and EEG abnormalities of several types. EEG biofeedback has been employed in conjunction with other therapies and may be useful in enhancing certain outcomes of therapy. Based on published clinical studies and employing efficacy criteria adapted by the Association for Applied Psychophysiology and Biofeedback and the International Society for Neurofeedback and Research, alpha theta training—either alone for alcoholism or in combination with beta training for stimulant and mixed substance abuse and combined with residential treatment programs, is probably efficacious. Considerations of further research design taking these factors into account are discussed and descriptions of contemporary research are given