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Koohi, Mahdi
- Satellite Images Edge Detection Based on Morphology Models Fusion
Abstract Views :466 |
PDF Views:119
Authors
Affiliations
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad university, Tehran, IR
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad university, Tehran, IR
Source
Indian Journal of Science and Technology, Vol 5, No 7 (2012), Pagination: 2997-3000Abstract
One of the first steps of feature extraction is edge detection. There are various methods for edge detection such as sobel operator, log method and canny operator but with disadvantages (create noise, image smoothing and discontinuous edge detected). We present an improved method for edge detection. In this method, edge detected by morphology's operator and their combination and with the use of various structure elements of images in satellite and remote sensing.Keywords
Satellite, Image Processing, Edge Detection, Multi Spectral ImagesReferences
- Aldo Cumani (1991) Edge detection in multi spectral images. Published CVGIP J. Graphical Models & Image Processing Archive. 53(1).
- Bakker WH and Schmidt KS (2002) Hyper spectral edge filtering for measuring homogeneity of surface cover types. Int. Instt. Aerospace Survey & Earth Sci., Hengelosestraat, The Netherlands.
- Beucher S (1990) Segmentation dimageset morphologiemath´ematique.Th`esededoctorat, ENSMP, Paris.
- CANTY (2002) Digital processing of multispectral images. Lecture Notes, Centerfor Remote Sensing on Land Appl., Univ.of Bonn.
- Christian Hergarten (2004) Investigations on land cover and land use of GornoBadakhshan (GBAO) by means of land cover classifications derived from LANDSAT 7 data making use of remote sensing and GIS techniques 2004.
- FOODY (2002) Status of land cover classification accuracy assessment. Remote Sensing of Environ. 80, 185–201.
- Image Processing Toolbox User’s Guide (2004) 8. Rafael A,.Gonzalez C, Richard B, Woods Steven E and Eddins L (2002) Digital image processing. 2nd ed.
- rnauMirTorres, Daniel Ruiz Aguilera, JoanTorrensSastre (2009) Image analysis applications of morphological operators based on uninorms. IFSA-EUSFLAT 2009.
- Santhaiah Ch, AnjanBabu G and UshaRani M (2009) Graylevel morphological operations for imagesegmentation and tracking edges on medical applications. IJCSNS Int. J. Comput. Sci. & Network Security..9(7).
- Zhao Yu-qian, Gui Wei-hua, Chen Zhen-cheng, Tang Jingtian and Li Ling-yun (2005) Medical images edge detection based on mathematical morphology. Proce. IEEE-EMBS. pp: 6492-6495.
- A Simulation Environment for Network Processor Based on Simultaneous Multi Thread Architecture
Abstract Views :499 |
PDF Views:97
Authors
Affiliations
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad university, Tehran, IR
2 Department I.E Engineering Sience&Technology, Mazandaran university, Mazandaran, IR
3 Department of electrical engineering, East Tehran Branch IslamicAzad University, Tehran, IR
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad university, Tehran, IR
2 Department I.E Engineering Sience&Technology, Mazandaran university, Mazandaran, IR
3 Department of electrical engineering, East Tehran Branch IslamicAzad University, Tehran, IR
Source
Indian Journal of Science and Technology, Vol 5, No 10 (2012), Pagination: 3384-3389Abstract
This study is centered on the architectural efficacy of network processors based on simultaneous multi thread (SMT) architecture that support multiple active concurrent hardware threads at the same time with the goal of sharing processor resources such as functional units and memory. This thread-level-parallelism can be exploited in packet processing devices called network processors. The programs running on network processors have different characteristics depending on where the processor is used and the input workload. In this paper , we introduce our simulation environment, called SNP (Simulator for Network Processor), for simulating a typical SMT network processor which includes a connected network controller and a packet generator. The simulator presented in this study is a process based "simulator for Network processor" (SNP) usable for different modes and applications based on "clock - by - clock" method and is described according to SMT Structure. The simulator architecture is performed by C++ language optimized as efficient as possible. Such simulator is similar with simple scalar simulator.Keywords
Network Processor, Router, Packet, Simulator, Architectural EfficacyReferences
- Burger D and Austin T (1997) The SimpleScalar Tool Set, v2.0. Technical Report UW-CS-97-1342, University of Winsconsin, Madison.
- CISCO (1999) Router architecture session 601, cisco system ,Inc,
- Franklin MA and Joshi V (2004) SimplePipe: a simulation tool for task allocation and design of processor pipelines with application to network processor. The IEEE Computer society 12th annual international symposium on modeling analysis and simulation of computer and telecommunications systems, Washington Univ., USA. pp: 59-66..
- Gries M, Kulkarni C, Sauer C and Keutzer K (2003) Comparing analytical modeling with simulation for network processor. Design Automation and Test in Europe Conference and Exhibition, California Univ., Berkeley ,CA ,USA. pp: 256-261.
- JianhuaHuang (2003) Network processor design, Proc. 5th Int. Conf. on ASIC2003, pp:26-33.
- Jing Fu Hagsand (2005) Designing and evaluating network processor applications. Workshop on high performance switching and routing. Institute of Technol. Kista, Sweden. pp:142-146.
- Lekkas P (2004) Network processor architectures, Protocol,platforms. McGraw-Hill.
- Niemann JG, Porrmam M and Ruckert U (2005) A scalable parallel SoC architecture for network processor. IEEE Computer society annual symposium on VLSI, Heinz Nixdorf Inst. Paderborn Univ., Germany, pp: 311-313.
- Noonan L (2004) Modeling a network processor using object oriented techniques. Euromicro Symposium on Digital System Design. Dept. of Electron. Eng. Limerrick Univ., Ireland. pp: 484-490.
- Spalink T, Karlin S, Peterson L and Gottlieb Y (2001) Building a robust software-based router using network processors. Proc. of the 18th ACM Symposium on Operating Systems Principles (SOSP01), Chateau Lake Louise, Banff, Alberta,Canada. October. pp:216-229,
- Wolf Tilman, Franklin mark (2006) Performance models for network processor design. IEEE Transact. on parallel and distributed systems.pp:548- 561.
- Wolf Tilman, Franklinmark E. Ayguade, Valero M and Navaux P (2006) A simulator for SMT architectures: Evaluating instruction cache topologies. 12th Symposium on Computer Architecture and High Performance Computing. pp: 279- 286.
- Object Tracking Based on Estimation Mesh Method
Abstract Views :332 |
PDF Views:87
Authors
Affiliations
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad university, Tehran, IR
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad university, Tehran, IR
Source
Indian Journal of Science and Technology, Vol 5, No 1 (2012), Pagination: 1851-1854Abstract
Object tracking is one of the most important problems in modern visual systems and researches are continuing their studies in this field. Mesh Method is regarded complicate for object tracking accompanied with many controversies and obstacles; but it may eliminate many problems and challenges in this field. In this tracking process, an effective and new algorithm is used for designing a concept based triangular two dimensional mesh considering locally equiangular property. This algorithm includes a non smooth selection process of a complex of nodes with a simple and fast star polygon based Triangulation methods which can cover all inter nod regions The basic point of this algorithm is to select a complex of nodes adapting mesh cells with the object borders and making a suitable correlation between nodes density and the level of local movements' changes. This algorithm is described and analyzed in detail and implemented in real time situation.Keywords
Tracking, Mesh Method, Prediction the Object Region, Estimation ObjectReferences
- Dabo Guo, Zhaoyang Lu and Xingxing Hu (2009) Content-based mesh design and occlusion adaptive GOP structure. IEEE Trans. Digital Image Processing. 6, 392-396.
- Gua Z (2001) Object detection and tracking in video. TR., Department of Computer Science, Kent State University.
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- Richard Szeliski (2006) Image alignment and stitching. Image Alignment and Stitching: A Tutorial Computer Graphics & Vision J. 2 (1),1-104.
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