Version-1 (May-June 2014)
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ABSTRACT:
In order to realize the rapid and accurate localization of multiple mobile robots under the global vision, a new visual segmentation algorithm based on the feedback adjustment of threshold is presented in paper. First, the position information of the mobile robots is described by the color label plates which are designed by ourselves; then, the improved grid method is used to search the color labels; finally, the segmentation threshold of the next frame image is adjusted based on the segmentation results of the mobile robots and the amount of noise in the current frame, and the visual localization of multiple mobile robots is realized through the self-adjusting thresh segmentation of color label plates. The experiment results show that the proposed method is characterized by small calculation amount, good real-time and strong noise suppression capability, performance and has strong noise suppression abilities, and the accurate visual localization of multiple mobile robots under the global vision can be realized.
Keywords: Feedback adjustment; Threshold segmentation; Grid method; Visual localization
Keywords: Feedback adjustment; Threshold segmentation; Grid method; Visual localization
[1]. J.L. Liu, Construction of RoboCup Small Size Soccer Robot Vision System, master's diss., Zhejiang University, Hangzhou, China, 2007.
[2]. Y.L. Zhu and X.M. Li, BP neural network based image segmentation technique for small sized league soccer robot team system, Journal of Mechanical & Electrical Engineering, 28(1), 2011, 79-82.
[3]. K. Qin, K. Xu, F.L. Liu and D.Y. Li, Image segmentation based on histogram analysis utilizing the cloud model, Computers & Mathematics with Applications, 62(7), 2011, 2824-2833.
[4]. S. Liu, Image segmentation technology of the Ostu method for image materials based on binary PSO algorithm, Advances in Intelligent and Soft Computing, 104,2011, 415-419.
[5]. X.J. Lei and A.L. Fu, 2-D maximum-entropy thresholding image segmentation method based on second-order oscillating PSO, Proc. 5th International Conference on Natural Computation, Tianjin, China, 2009, 161-165.
[2]. Y.L. Zhu and X.M. Li, BP neural network based image segmentation technique for small sized league soccer robot team system, Journal of Mechanical & Electrical Engineering, 28(1), 2011, 79-82.
[3]. K. Qin, K. Xu, F.L. Liu and D.Y. Li, Image segmentation based on histogram analysis utilizing the cloud model, Computers & Mathematics with Applications, 62(7), 2011, 2824-2833.
[4]. S. Liu, Image segmentation technology of the Ostu method for image materials based on binary PSO algorithm, Advances in Intelligent and Soft Computing, 104,2011, 415-419.
[5]. X.J. Lei and A.L. Fu, 2-D maximum-entropy thresholding image segmentation method based on second-order oscillating PSO, Proc. 5th International Conference on Natural Computation, Tianjin, China, 2009, 161-165.
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ABSTRACT: Ultrasound imaging is the most commonly used imaging system for disease diagnosis. Speckle noise is an inherent property of medical ultrasound imaging. Since speckle may hinder the detection of image details it is typically regarded as noise and there is a strong need to remove speckle effectively for good and fast interpretation. Multiresolution analysis is the important tool in eliminating noise from images effectively. In this paper an algorithm is proposed that uses multiresolution analysis through which it is possible to distinguish noise and image information better than at one resolution level. The proposed algorithm combines the features of filtering techniques in multiresolution framework to combine the benefits that each one can contribute. This algorithm maintains a balance between speckle suppression and feature preservation. The result is shown to be promising and outperforms other despeckling approaches. Performance evaluations are performed by using statistical parameters like Mean Square Error (MSE), Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR), Speckle Index (SI) and Edge Preservation Index (EPI).
Keywords: Ultrasound imaging, Speckle noise, Multiresolution, PSNR, SI, EPI.
Keywords: Ultrasound imaging, Speckle noise, Multiresolution, PSNR, SI, EPI.
[1] Irraivan Elamvazuthi Muhammad Luqman Bin Muhd Zain,K.M.Begam "Despeckling of ultrasound images of bone fracture using multiple filtering algorithm", ELSEVIER, Mathematical and Computer Modelling57(2013)152-168.
[2] Muhammad Luqman Bin Muhd Zain, Irraivan Elamvazuthi and Mumtaj Begam,"Enhancement of Bone Fracture Image Using Filtering Techniques", The International Journal of Video & Image Processing and Network Security Vol:9 No:10
[3] Bobby and Manish Mahajan, "Performance Comparison Between Filters and Wavelet Transform in Image Denoising for Different Noises" International Journal of Computer Science and Communication.
[4] K.Karthikeyan, Dr.C. Chandrasekar,"Speckle Noise Reduction of Medical Ultrasound Images using Bayesshrink Wavelet Threshold", International journal of Computer Applications (1975-8887)Volume 22-No.9, May 2011.
[5] Juan L.Mateo,Antonio Fernandez-Caballero" Finding out general tendencies in speckle noise reduction in ultrasound images" ELSEVIER, Expert systems with applications 2009.
[2] Muhammad Luqman Bin Muhd Zain, Irraivan Elamvazuthi and Mumtaj Begam,"Enhancement of Bone Fracture Image Using Filtering Techniques", The International Journal of Video & Image Processing and Network Security Vol:9 No:10
[3] Bobby and Manish Mahajan, "Performance Comparison Between Filters and Wavelet Transform in Image Denoising for Different Noises" International Journal of Computer Science and Communication.
[4] K.Karthikeyan, Dr.C. Chandrasekar,"Speckle Noise Reduction of Medical Ultrasound Images using Bayesshrink Wavelet Threshold", International journal of Computer Applications (1975-8887)Volume 22-No.9, May 2011.
[5] Juan L.Mateo,Antonio Fernandez-Caballero" Finding out general tendencies in speckle noise reduction in ultrasound images" ELSEVIER, Expert systems with applications 2009.
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ABSTRACT: This is a review paper in which we use various techniques for low power optimization and with the help of these techniques we perform comparative analysis. Evolution in VLSI continuously reduce the silicon technology to fulfill the increasing demands for higher functionality, low power and better performance at low cost. In today's scenario, low power design becomes an important issue. Most of the power consumption takes place during switching events i.e. dynamic power. This paper present various basic circuit in which reduction in power consumption takes place due to transistor sizing as well as MTCMOS technique separately and then we will also design the same circuit by the combination of the above two techniques which consume overall less power than conventional CMOS circuitry. Basic circuit are fundamental components of any digital design. We also see the effect of voltage scaling on these circuit and reduce the circuit using shannon's expansion theorem without changing in functionality ,to reduce the transistor count so that power decrease. The investigation has been carried out with simulation run environment on cadence virtuoso design editor using 180nm CMOS process technology at 1.8 V.
Keywords: MTCMOS, transistor sizing, Combined MTCMOS & transistor sizing, shannon's expansion theorem
Keywords: MTCMOS, transistor sizing, Combined MTCMOS & transistor sizing, shannon's expansion theorem
[1] Raju Gupta, Satya Prakash Pandey ,Shyam Akashe ,Abhay Vidyarthi, "Analysis and Optimization of Active Power and Delay of 10T Full Adder using Power Gating Technique at 45nm Technology," IOSR Journal of VLSI and Signal Processing(IOSR-JVSP), vol.2, pp 51-57, April2013.
[2] Geetha Priya, K.Baskaran," Low Power Full Adder with Reduced Transistor Count," International Journal of Engineering Trends and Technology (IJETT), vol.4, May2013.
[3] Karthik Reddy.G," Low Power –Area Designs of 1 Bit Full Adder in Cadence Virtuoso Platform, "International Journal of VLSI design &Communication Systems (VLSICS), vol.4, No.4, August2013.
[4] P.Sreenivasulu,G.Vinatha,Dr.K.SrinivasaRao,Dr.A.VinayaBabu,"Novel Ultra Low Power Multi threshold CMOS Technology," International Journal of Advanced Research in Computer Science and Software Engineering,vol.3,pp.81-88,Aug 2013.
[5] Jatinder Kumar, Praveen Kaur ,"Comparative Performance Analysis of Different CMOS Adders using 90nm and 180 nm Technology," International Journal of Advanced Research in Computer Engineering and Technology, vol.2, August2013.
[2] Geetha Priya, K.Baskaran," Low Power Full Adder with Reduced Transistor Count," International Journal of Engineering Trends and Technology (IJETT), vol.4, May2013.
[3] Karthik Reddy.G," Low Power –Area Designs of 1 Bit Full Adder in Cadence Virtuoso Platform, "International Journal of VLSI design &Communication Systems (VLSICS), vol.4, No.4, August2013.
[4] P.Sreenivasulu,G.Vinatha,Dr.K.SrinivasaRao,Dr.A.VinayaBabu,"Novel Ultra Low Power Multi threshold CMOS Technology," International Journal of Advanced Research in Computer Science and Software Engineering,vol.3,pp.81-88,Aug 2013.
[5] Jatinder Kumar, Praveen Kaur ,"Comparative Performance Analysis of Different CMOS Adders using 90nm and 180 nm Technology," International Journal of Advanced Research in Computer Engineering and Technology, vol.2, August2013.
