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Sinhgad College of EngineeringDepartment of Information Technology
Project ReviewOn
Design And Implementation Of Database ForWildlife Sanctuary
by
3 Sep 2012
Guide
Prof. A. A. Agarkar
Roll No Name
407022 Rameshwar Gangane
407027 Akshay Ingle
407038 Rahul Katole
407157 Pritamkumar Tayde
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Design And Implementation Of
Database For Wildlife Sanctuary Project Area : System Based, Multimedia, DBMS,
Video Processing.
Sponsorship : No
External Guide : N/A
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Aim and Objectives
The Aim of this project is to design and implement databaseto store, index, search and retrieve the data from wildlifesanctuary.
Objectives:
Building a database.
Building a software framework.
Indexing of the data.
Retrieval of the information.
The major target is:
Building the image retrieval system
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Literature Survey 1/2
In 1979, a conference on Database Techniques for
Pictorial Applications was held in Florence.
In 1992, national Science Foundation of the US organized
a workshop. A.W.M.Smeulders[5] has provided the steps carried out
in content based image retrieval process.
Subrahmanyam Murala [1] presented a novel image
indexing and retrieval algorithm by grey-level difference.
Tai X.Y in his paper has given the use of content based
image retrieval systems in the Medical field.
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Literature Survey 2/2
QBIC is query by image content by IBM [8] , MIT
Photobook are earliest systems.
In the academic domain T.J. Watson, VIR,AMORE, and
Bell Laboratory WALRUS. Berkeley Blobworld, Columbia Visualseek and Webseek ,
Natra, and Stanford WBIIS are some of the recent well
known systems.
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Design and Implementation Of DataWarehouse For Wildlife Sanctuary
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We are implementing database for handling data.
This system works in three phases.
Building database
Input to the system
Retrieval of the information
For retrieval of these data we are building intelligent
image retrieval system.
Problem statement
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Preferred Technology
These are the preferred technologies:
SUN JAVA
Net Beans/Eclipse(IDE)
Oracle Xg SQL
SQL queries
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Hardware and Software Requirements
Hardware :
Processor : Pentium IV and onwards
RAM : 1 GB(minimum)
HDD : 1 GB onwards
Software : JDK 1.6, Net Beans/Eclipse(IDE)
Libraries : JMF(Java Media framework).
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Scope of the project
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Retrieval
Feature Extraction
Matching Similarity
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D/W
Server
IndexingInput
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Design of project 1/2
Modules
Administrator moduleo Manage the database.
User moduleo Provide the query.
o Gets the results.
Searching moduleo Extract the features.
o Measures the similarity.
o Indexing and retrieval.
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Design of project 2/2
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CBIR block diagram
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Data Flow Diagram 1/3
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LEVEL 0
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Data Flow Diagram 2/3
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LEVEL 1
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Data Flow Diagram 3/3
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LEVEL 2
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Use Case Diagram
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Plan of a project
PERT Chart
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Conclusion
This project is undertaken to design database for
wildlife sanctuary which will help in getting
information.
We are building query base as well as content base
retrieval system.
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[1] Subrahmanyam Murala, R. P. Maheshwari, and R. Balasubramanian,
Local Tetra Patterns: A New Feature Descriptor for Content -Based
Image Retrieval, IEEE Trans. Image Process., vol. 21, no. 5, pp.
28742886, May 2012 [2] Gang Luo, Rong Yan, Phillip you Real Time new
even Detection for video streams, . IBM T.J. Watson Research Center,2008.[3] Sirirut Vanichayobon,Lee Gruenwald Indexing Techinques for data
warehouses queries,2008
[4] Chuck Bollard, Don Schau Data Modeling Techniques for Data
Warehousing ,International Technical support organization,2002.
[5] Smeulders.A.W.M, Worring.M, Santini.S,Gupta.A, and R. Jain,Content- based image retrieval at the end of the early years, IEEE
Trans. Pattern Anal.Mach. Intell.,vol. 22, no. 12, pp. 13491380,
Dec. 2000
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References1/2
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[6] Tai X. Y., Wang L. D. , Medical Image Retrieval Based on Color-
Texture Algorithm and GTI Model, Bioinformatics and Biomedical
Engineering, 2008, ICBBE 2008, The 2nd International Conference
on, pp. 2574-2578.
*7+ R. Zhang, and Z. Zhang, A Clustering Based Approach to Efficient ImageRetrieval, Proceedings of the 14th IEEE International Conference on Tools
with Artificial Intelligence (ICTAI02), Washington, DC, Nov. 2002, pp. 339-346.
[8] M. Flickner, H. Sawhney, W. Niblack, J. Ashley, Q. Huang, B. Dom, M. Gorkani,J.
Hafner, D. Lee, D. Petkovic, and P. Yanker, Query by image and video
content:The QBIC system, IEEE Computer, vol. 28, no 9, pp.23-32, Sep. 1995.
[9]
References 2/2
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THANK YOU
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