How to search?
advanced search

Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 4
items per page: 25 50 75
Sort by:

Thermal analysis of generalized Burgers nanofluid over a stretching sheet with nonlinear radiation and non uniform heat source/sink

Ganesh Kumar K. B.J. Gireesha G.K. Ramesh
Archives of Thermodynamics | 2018 | vol. 39 | No 2
Keywords Burgers nanofluid Non-uniform heat source/sink Non-linear radiation Magnetic field Stretching surface
Download PDF Download RIS Download Bibtex

Abstract

The work deals with the heat analysis of generalized Burgers nanofluid over a stretching sheet. The Rosseland approximation is used to model the non-linear thermal radiation and incorporated non-uniform heat source/sink effect. The governing equations reduced to a set of nonlinear ordinary differential equations under considering the suitable similarity transformations. The obtained ordinary differential equations equations are solved numerically by Runge-Kutta-Fehlberg order method. The effect of important parameters on velocity, temperature and concentration distributions are analyzed and discussed through the graphs. It reveals that temperature increases with the increase of radiation and heat source/sink parameter.
Go to article

Authors and Affiliations

Ganesh Kumar K.
B.J. Gireesha
G.K. Ramesh

Mass transfer analysis of two-phase flow in a suspension of microorganisms

S.U. Mamatha K. Ramesh Babu P. Durga Prasad C.S.K. Raju S.V.K. Varma
Archives of Thermodynamics | 2020 | vol. 41 | No 1 | 175-192 | DOI: 10.24425/ather.2020.132954
Keywords Gyrotactic microorganisms Dusty fluid Mass transfer Stretching sheet Bio convection Boundary layer flow
Download PDF Download RIS Download Bibtex

Abstract

The aim of present work is to investigate the mass transfer of steady incompressible hydromagnetic fluid near the stagnation point with deferment of dust particles over a stretching surface. Most researchers tried to improve the mass transfer by inclusion of cross-diffusion or dust particles due to their vast applications in industrial processes, extrusion process, chemical processing, manufacturing of various types of liquid drinks and in various engineering treatments. To encourage the mass transport phenomena in this study we incorporated dust with microorganisms. Conservation of mass, momentum, concentration and density of microorganisms are used in relevant flow equations. The arising system of nonlinear partial differential equations is transformed into nonlinear ordinary differential equations. The numerical solutions are obtained by the Runge-Kutta based shooting technique and the local Sherwood number is computed for various values of the physical governing parameters (Lewis number, Peclet number, Eckert number). An important finding of present work is that larger values of these parameters encourage the mass transfer rate, and the motile organisms density profiles are augmented with the larger values of fluid particle interaction parameter with reference to bioconvection, bioconvection Lewis number, and dust particle concentration parameter.

Go to article

Authors and Affiliations

S.U. Mamatha
K. Ramesh Babu
P. Durga Prasad
C.S.K. Raju
S.V.K. Varma

Lane Detection by Dynamic Origin Technique for Advanced Driver Assistance System

P. Maya C. Tharini
International Journal of Electronics and Telecommunications | 2021 | vol. 67 | No 4 | 589-594 | DOI: 10.24425/ijet.2021.137850
Keywords Advanced Driver Assistance System (ADAS) Machine Vision Research Lane Detection Piecewise Linear Stretching Function Slope Detection
Download PDF Download RIS Download Bibtex

Abstract

Lane detection is one of the key steps for developing driver assistance and vehicle automation features. A number of techniques are available for lane detection as part of computer vision tools to perform lane detection with different levels of accuracies. In this paper a unique method has been proposed for lane detection based on dynamic origin (DOT). This method provides better flexibility to adjust the outcome as per the specific needs of the intended application compared to other techniques. As the method offers better degree of control during the lane detection process, it can be adapted to detect lanes in varied situations like poor lighting or low quality road markings. Moreover, the Piecewise Linear Stretching Function (PLSF) has also been incorporated into the proposed method to improve the contrast of the input image source. Adding the PLSF method to the proposed lane detection technique, has significantly improved the accuracy of lane detection when compared to hough transform method from 87.88% to 98.25% in day light situations and from 94.15% to 97% in low light situations.
Go to article

Bibliography

[1] V. Gaikwad, S. Lokhande, “Lane departure identification for advanced driver assistance,” IEEE Transactions on Intelligent Transportation Systems., 2015, 16(2): 910–918.
[2] Sandipann P. Narote, Pradnya N. Bhujbal, Abbhilasha S. Narote, Dhiraj M. Dhane, “A review of recent advances in lane detection and departure warning,” System. Pattern Recognition, 2018, 73:216-234.
[3] P.C. Wu, C. Chang, C.H. Lin, “Lane mark extraction for automobiles under complex conditions,” Pattern Recognition, 2014, 47: 2756–2767.
[4] C. Mu, X. Ma, “Lane detection based on object segmentation and piecewise fitting,” Telkomnika Indonesian Journal of Electrical Engineering, 2014, 12(5):3491–3500.
[5] CALTECH database http://www.vision.caltech.edu/archive.html
[6] Y. Dong, J. Xiong, L. Li, J. Yang “Lane detection based on object segmentation and piecewise fitting,” ICCP proceedings, 2012, 461–464.
[7] P. Hsiao, C.W. Yeh, S. Huang, L.C. Fu, “Portable vision based real time lane departure warning system day and night,” IEEE Transactions on Vehicular Technology,2009, 58(4):2089–2094.
[8] Prashanth Viswanath, Pramod Swami, “A Robust and Real -Time Image Based Lane Departure Warning System,” IEEE International Conference on Consumer Electronics, 2016.
[9] Minghua Niu, Jianmin Zhang, Gen Li, “Research on the Algorithms of Lane Recognition based on Machine Vision,” International Journal of Intelligent Engineering and Systems, 2015, 8(4).
[10] Gulivindala Suresh,Chanamallu Srinivasa Rao, “Localization of Copy-Move Forgery in Digital Images through Differential Excitation Texture Features,” International Journal of Intelligent Engineering and Systems, 2019, 12(2).
[11] C.R. Jung, C.R. Kelber, “Lane following and lane departure using a linear parabolic mode,” Image and Vision Computing, 2005, 23(13):1192–1202.
[12] D. Kragic, L. Petersson and H.I. Christensen, “Visually guided manipulation tasks,” Robotics and Autonomous Systems, 2002, 40(2/3):193-203.
[13] J.W. Lee, “A machine vision system for lane departure detection. Computing,” Vision Image Understanding, 2002, 86(1): 52–78.
[14] J. Melo, A. Naftel, A. Bernardino, J. Santos, “Detection and classification of highway lanes using vehicle motion trajectories,” IEEE Transactions on Intelligent Transportation Systems, 2006, 7(2): 188–200.
[15] Chaiwat Nuthong; Theekapun Charoenpong, “Lane detection using smoothing,” 3rd International Congress on Image and Signal Processing, 2010, 989-993.
[16] Bing Yu; Weigong Zhang; Yingfeng Cai, “A Lane Departure Warning System Based on Machine Vision,” Proceeding IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application, 2008, 197-201.
[17] J.G. Wang, C. Lin, S. Chen, “Applying fuzzy method to vision-based lane detection and departure warning system,” Expert Systems with Applications, 2010, 3(1):113–126.
[18] H. Xu, H. Li, “Study on a robust approach of lane departure warning algorithm,” IEEE International Conference on Signal Processing System (ICSPS), 2010, 201–204.
[19] S. Srivastava, M. Lumb, R. Singal, “Improved Lane Detection using Hybrid Median Filter and Modified Hough Transform,” International Journal of Advanced Research in Computer Science and Software Engineering, 2014, 4(1): 30–37.
[20] H. Aung, M.H. Zaw, “Video based lane departure warning system using hough transform,” International Conference on Advances in Engineering and Technology (ICAET), 2010, 85–88.
[21] X. An, E. Shang, J. Song, J. Li, H. He, “Real-time lane departure warning system based on a single fpga,” Eurasip Journal on Image and Video Processing, 2013,38(1–18).
[22] J. Son, H. Yoo, S. Kim, K. Sohn, “Real-time illumination invariant lane detection for lane departure warning system,” Expert Systems with Applications, 2015, 42(4):1816–1824.
[23] Y. Wang, D. Shen, E.K. Teoh, “Lane detection using spline model,” Pattern Recognition, 2000, 21(9): 677–689.
[24] C.J. Lin, J.G. Wang, S.M. Chen, C.Y. Lee, “Design of a lane detection and departure warning system using functional link-based neuro-fuzzy network,” IEEE International Conference on Fuzzy System (FUZZ), 2010, 1–7.
[25] Q. Lin, Y. Han, H. Hahn, “Real time lane detection based on extended edge-linking algorithm,” IEEE International Conference on Computer Research and Development, 2010, 725–730.
[26] C. Tu, B.V. Wyk, Y. Hamam, K. Djouni, S. Du, “Vehicle Position Monitoring using,” Hough Transform.IERI Procedia, 2013;4:316–322.
[27] E. Salari, D. Ouyang, “Camera-based forward collision and lane departure warning system using svm,” IEEE 56th International Midwest Symp. On Circuits and Systems (MWSCAS), 2013,1278–1281.
[28] A.S. Aguadoa, Eugenia, Montie and M. S. Nixonc, “Invariant characterisation of the Hough transform for pose estimation of arbitrary shapes,” Pattern Recognition, 2002, 35(5):1083-1097.
[29] Borkar, M. Hayes, M. Smith, “Robust lane detection and tracking with ransac and kalman filter,” 16th IEEE International Conference on Image Processing (ICIP), 2009, 3261–3264.
[30] N. Madrid, P. Hurtik “Lane departure warning for mobile devices based on a fuzzy representation of images,” Fuzzy Sets System, 2016, 291:144–159.
[31] P.Maya, C.Tharini, “Performance Analysis of Lane Detection Algorithm using Partial Hough Transform,” 21st International Arab Conference on Information Technology (ACIT'2020), 2020, Egypt.
Go to article

Authors and Affiliations

P. Maya
1
C. Tharini
2
  1. B S Abdur Rahman Crescent Institute of Science and Technology, Chennai, India
  2. B S Abdur Rahman Crescent Institute of Science and Technology,Chennai, India

3D face reconstruction with region based best fit blending using mobile phone for virtual reality based social media

G. Anbarjafari R.E. Haamer I. Lüsi T. Tikk L. Valgma
Bulletin of the Polish Academy of Sciences Technical Sciences | 2019 | 67 | No. 1 | 125-132
Keywords facial modeling morphing stretching computer vision similarity calculation deformable model 3D faces virtual reality blendshape
Download PDF Download RIS Download Bibtex

Abstract

The use of virtual reality (VR) has been exponentially increasing and due to that many researchers have started to work on developing new VR based social media. For this purpose it is important to have an avatar of the user which look like them to be easily generated by the devices which are accessible, such as mobile phones. In this paper, we propose a novel method of recreating a 3D human face model captured with a phone camera image or video data. The method focuses more on model shape than texture in order to make the face recognizable. We detect 68 facial feature points and use them to separate a face into four regions. For each area the best fitting models are found and are further morphed combined to find the best fitting models for each area. These are then combined and further morphed in order to restore the original facial proportions. We also present a method of texturing the resulting model, where the aforementioned feature points are used to generate a texture for the resulting model.

Go to article

Authors and Affiliations

G. Anbarjafari
R.E. Haamer
I. Lüsi
T. Tikk
L. Valgma

This page uses 'cookies'. Learn more