scholarly journals COMPUTATIONLESS PALM-PRINT VERIFICATION USING WAVELET ORIENTED ZERO-CROSSING SIGNATURE

2022 ◽  
Vol 23 (1) ◽  
pp. 222-232
Author(s):  
Jitendra Chaudhari ◽  
Hiren Mewada ◽  
Amit Patel ◽  
Keyur Mahant ◽  
Alpesh Vala
Keyword(s):  
Euclidean Distance ◽  
Vertical Direction ◽  
Texture Features ◽  
Discrete Wavelet ◽  
Transform Domain ◽  
Recognition Time ◽  
Zero Crossing ◽  
Palm Print ◽  
Best Fit

Palmprints can be characterized by their texture and the patterns of that texture dominate in a vertical direction. Therefore, the energy of the coefficients in the transform domain is more concentrated in the vertical sideband. Using this idea, this paper proposes the characterization of the texture features of the palmprint using zero-crossing signatures based on the dyadic discrete wavelet transform (DWT) to effectively identify an individual. A zero-crossing signature of 4 x 256 was generated from the lower four resolution levels of dyadic DWT in the enrolment process and stored in the database to identify the person in recognition mode. Euclidean distance was determined to find the best fit for query palmprints zero-crossing signature from the dataset. The proposed algorithm was tested on the PolyU dataset containing 6000 multi-spectral images. The proposed algorithm achieved 96.27% accuracy with a lower recognition time of 0.76 seconds. ABSTRAK: Pengesan Tapak Tangan boleh dikategorikan berdasarkan ciri-ciri tekstur dan corak pada tekstur yang didominasi pada garis tegak. Oleh itu, pekali tenaga di kawasan transformasi adalah lebih penuh pada jalur-sisi menegak. Berdasarkan idea ini, cadangan kajian ini adalah berdasarkan ciri-ciri tekstur pada tapak tangan dan tanda pengenalan sifar-silang melalui transformasi gelombang kecil diadik yang diskret (DWT) bagi mengecam individu. Pada mod pengecaman, tanda pengenalan sifar-silang 4 x 256 yang terhasil daripada tahap diadik resolusi empat terendah DWT digunakan dalam proses kemasukan dan simpanan di pangkalan data bagi mengenal pasti individu. Jarak Euklidan yang terhasil turut digunakan bagi memperoleh padanan tapak tangan paling sesuai melalui tanda pengenalan sifar-silang dari set data.  Algoritma yang dicadangkan ini diuji pada set data PolyU yang mengandungi 6000 imej pelbagai-spektrum. Algoritma yang dicadangkan ini berjaya mencapai ketepatan sebanyak 96.27% dengan durasi pengecaman berkurang sebanyak 0.76 saat.

Improving the Computational Cost for Copied Region Detection in Forensic Images

2016 ◽  
Vol 2 (1) ◽  
pp. 55
Author(s):  
Tu Huynh-Kha ◽  
Thuong Le-Tien ◽  
Synh Ha ◽  
Khoa Huynh-Van
Keyword(s):  
Wavelet Transform ◽  
Euclidean Distance ◽  
Research Work ◽  
Computational Cost ◽  
Correlation Coefficients ◽  
Zernike Moments ◽  
Computational Time ◽  
Discrete Wavelet ◽  
Feature Vectors ◽  
Region Detection

This research work develops a new method to detect the forgery in image by combining the Wavelet transform and modified Zernike Moments (MZMs) in which the features are defined from more pixels than in traditional Zernike Moments. The tested image is firstly converted to grayscale and applied one level Discrete Wavelet Transform (DWT) to reduce the size of image by a half in both sides. The approximation sub-band (LL), which is used for processing, is then divided into overlapping blocks and modified Zernike moments are calculated in each block as feature vectors. More pixels are considered, more sufficient features are extracted. Lexicographical sorting and correlation coefficients computation on feature vectors are next steps to find the similar blocks. The purpose of applying DWT to reduce the dimension of the image before using Zernike moments with updated coefficients is to improve the computational time and increase exactness in detection. Copied or duplicated parts will be detected as traces of copy-move forgery manipulation based on a threshold of correlation coefficients and confirmed exactly from the constraint of Euclidean distance. Comparisons results between proposed method and related ones prove the feasibility and efficiency of the proposed algorithm.

scholarly journals UAV Recognition Based on Micro-Doppler Dynamic Attribute-Guided Augmentation Algorithm

2021 ◽  
Vol 13 (6) ◽  
pp. 1205
Author(s):  
Caidan Zhao ◽  
Gege Luo ◽  
Yilin Wang ◽  
Caiyun Chen ◽  
Zhiqiang Wu
Keyword(s):  
Recognition Performance ◽  
Principal Component ◽  
Texture Features ◽  
Training Model ◽  
Recognition Algorithm ◽  
Discrete Wavelet ◽  
Dynamic Feature ◽  
Complex Environments ◽  
Time Frequency ◽  
Model Training

A micro-Doppler signature (m-DS) based on the rotation of drone blades is an effective way to detect and identify small drones. Deep-learning-based recognition algorithms can achieve higher recognition performance, but they needs a large amount of sample data to train models. In addition to the hovering state, the signal samples of small unmanned aerial vehicles (UAVs) should also include flight dynamics, such as vertical, pitch, forward and backward, roll, lateral, and yaw. However, it is difficult to collect all dynamic UAV signal samples under actual flight conditions, and these dynamic flight characteristics will lead to the deviation of the original features, thus affecting the performance of the recognizer. In this paper, we propose a small UAV m-DS recognition algorithm based on dynamic feature enhancement. We extract the combined principal component analysis and discrete wavelet transform (PCA-DWT) time–frequency characteristics and texture features of the UAV’s micro-Doppler signal and use a dynamic attribute-guided augmentation (DAGA) algorithm to expand the feature domain for model training to achieve an adaptive, accurate, and efficient multiclass recognition model in complex environments. After the training model is stable, the average recognition accuracy rate can reach 98% during dynamic flight.

Characterization of the morning transition from downslope to upslope winds and its connection with the nocturnal inversion breakup at the foot of a gentle slope

2021 ◽  
Author(s):  
Sofia Farina ◽  
Dino Zardi ◽  
Silvana Di Sabatino ◽  
Mattia Marchio ◽  
Francesco Barbano
Keyword(s):  
Salt Lake ◽  
Vertical Direction ◽  
Blow Down ◽  
Physical Mechanisms ◽  
Morning Transition ◽  
Thermally Driven ◽  
Slope Wind ◽  
Slope Flow ◽  
Nocturnal Inversion

<p>Thermally driven winds observed in complex terrain are characterized by a daily cycle dominated by two main phases: a diurnal phase in which winds blow upslope (anabatic), and a nocturnal one in which they revert their direction and blow down slope (katabatic). This alternating pattern also implies two transition phases, following sunrise and sunset respectively. </p><p>Here we study the up-slope component of the slope wind with a focus on the morning transition based on from the MATERHORN experiment, performed in Salt Lake Desert (Utah) between Fall 2012 and Spring 2013. </p><p>The analysis develops along three main paths of investigation. The first one is the selection of the suitable conditions for the study of the diurnal component and the characterization of the morning transition. The second one focuses on the deep analysis of the erosion of the nocturnal inversion at the foot of the slope in order to investigate the physical mechanisms driving it. And the third one consists in the comparison between the experimental data and the results of an analytical model (Zardi and Serafin, 2015). The study of the morning transition in the selected case studies allowed its characterization in terms of the relation with the solar radiation cycle, in terms of its seasonality and in terms of its propagation along the slope and along the vertical direction. Most of the results of this investigation are related to the identification of the main mechanisms of erosion of the nocturnal inversion at the foot of the slope and to its role to the beginning of the transition itself. Finally, it is shown how the above model can fairly reproduce the cycle between anabatic and katabatic flow and their intensity.</p><p>Zardi, D. and S. Serafin, 2015: An analytic solution for daily-periodic thermally-driven slope flow. Quart. J. Roy. Meteor. Soc., 141, 1968–1974.</p>

scholarly journals Image Denoising Using Discrete Wavelet Transform : A Theoretical Framework

2018 ◽  
Vol 7 (2.16) ◽  
pp. 120
Author(s):  
Praveen Bhargava ◽  
Shruti Choubey ◽  
Rakesh Kumar Bhujade ◽  
Nilesh Jain
Keyword(s):  
Image Denoising ◽  
Ultra Sound ◽  
Discrete Wavelet ◽  
Transform Domain ◽  
Hybrid Filter ◽  
Edge Sharpness ◽  
In Series ◽  
Salt And Pepper ◽  
Image Type

Noise is a random variation in brightness and color in image or simply we can say that unwanted signals are called noise. The noise is mixed with original signal and cause may troubles. Due to the presence of noise, quality of image is reduced and other features like edge sharpness and pattern recognition are badly affected. In image denoising methods to improve the results a hybrid filter is used for better visualization. The hybrid filter is composed with the combination of three filters connected in series. The hybridization has performed much better in case of salt and pepper type of noise and for most of the medical image type, either MRI, CT, SPECT, Ultra Sound. PSNR values show major improvement in comparison of other existing methods. Future, the results obtained from the presented denoising experiments would be tried to be improved further by using this method with other transform domain methods. Finally, the results are concluded that the proposed approach in terms of PSNR, MSE improvement is outperformed. 

Characterization of a TTX-sensitive Na+ current in pacemaker cells isolated from rabbit sinoatrial node

1996 ◽  
Vol 270 (6) ◽  
pp. H2108-H2119 ◽  
Author(s):  
H. Muramatsu ◽  
A. R. Zou ◽  
G. A. Berkowitz ◽  
R. D. Nathan
Keyword(s):  
Action Potential ◽  
Ventricular Myocytes ◽  
Pacemaker Cells ◽  
Na Current ◽  
Recovery From Inactivation ◽  
Cell Recording ◽  
Rabbit Sinoatrial Node ◽  
Best Fit ◽  
Maximum Conductance

A tetrodotoxin (TTX)-sensitive Na+ current (iNa) was investigated in single pacemaker cells after 1-4 days in culture. Ruptured-patch and perforated-patch whole cell recording techniques were used to record iNa and spontaneous electrical activity, respectively. For seven cells exposed to 20 mM Na+ (22-24 degrees C) and held at -98 mV (25% of the channels inactivated), the uncorrected maximum iNa was -39 +/- 10 pA/pF at -29.1 +/- 2.4 (SE) mV, maximum conductance was 0.9 +/- 0.2 nS/pF (1.6 +/- 0.2 mS/cm2). Half-activation and inactivation potentials were -41.4 +/- 2.0 and -90.6 +/- 2.5 mV, and the corresponding slope factors were 6.0 +/- 0.4 and 6.4 +/- 0.6 mV. Inactivation and recovery from inactivation were best fit by sums of two exponentials. During action potential clamp, a TTX-sensitive compensation current accounted for 55% of the upstroke velocity. The results suggest that iNa contributes significantly to the action potential in some nodal pacemaker cells, and the characteristics of iNa are similar to those of atrial and ventricular myocytes.

scholarly journals HUMAN IDENTIFICATION BASED ON FACE RECOGNITION SYSTEM

2021 ◽  
Vol 25 (01) ◽  
pp. 80-91
Author(s):  
Saba K. Naji ◽  
◽  
Muthana H. Hamd ◽  
Keyword(s):  
Face Recognition ◽  
Euclidean Distance ◽  
Local Binary Pattern ◽  
Texture Features ◽  
Recognition System ◽  
Manhattan Distance ◽  
Distance Measurements ◽  
Local Ternary Pattern ◽  
Face Recognition System ◽  
Cosine Distance

Due to, the great electronic development, which reinforced the need to define people's identities, different methods, and databases to identification people's identities have emerged. In this paper, we compare the results of two texture analysis methods: Local Binary Pattern (LBP) and Local Ternary Pattern (LTP). The comparison based on comparing the extracting facial texture features of 40 and 401 subjects taken from ORL and UFI databases respectively. As well, the comparison has taken in the account using three distance measurements such as; Manhattan Distance (MD), Euclidean Distance (ED), and Cosine Distance (CD). Where the maximum accuracy of the LBP method (99.23%) is obtained with a Manhattan and ORL database, while the LTP method attained (98.76%) using the same distance and database. While, the facial database of UFI shows low quality, which is satisfied 75.98% and 73.82% recognition rates using LBP and LTP respectively with Manhattan distance.

scholarly journals Secure Data Transfer over Internet Using Image Steganography: Review

2021 ◽  
pp. 33-52
Author(s):  
Dakhaz Mustafa Abdullah ◽  
Siddeeq Y. Ameen ◽  
Naaman Omar ◽  
Azar Abid Salih ◽  
Dindar Mikaeel Ahmed ◽  
...  
Keyword(s):  
Digital Media ◽  
Private Information ◽  
Data Transfer ◽  
Well Being ◽  
Discrete Wavelet ◽  
Transform Domain ◽  
Least Significant Bit ◽  
Discrete Cosine Transformation ◽  
Hide Information ◽  
Pixel Value

Whether it's for work or personal well-being, keeping secrets or private information has become part of our everyday existence. Therefore, several researchers acquire an entire focus on secure transmitting secret information. Confidential information is collectively referred to as Steganography for inconspicuous digital media such as video, audio, and images. In disguising information, Steganography plays a significant role. Traditional Steganography faces a further concern of discovery as steganalysis develops. The safety of present steganographic technologies thus has to be improved. In this research, some of the techniques that have been used to hide information inside images have been reviewed. According to the hiding domain, these techniques can be divided into two main parts: The spatial Domain and Transform Domain. In this paper, three methods for each Domain have been chosen to be studied and evaluated. These are; Least Significant Bit (LSB), Pixel Value Difference (PVD), Exploiting Modification Direction (EMD), contourlet transform, Discrete Wavelet Transformation (DWT), and, Discrete Cosine Transformation (DCT). Finally, the best results that have been obtained in terms of higher PSNR, Capacity, and more robustness and security are discussed.

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