DEVELOPMENT OF A STANDALONE APPLICATION FOR UNSUPERVISED IMAGE CLASSIFICATION

  • Type: Project
  • Department: Geography
  • Project ID: GEO0051
  • Access Fee: ₦5,000 ($14)
  • Pages: 102 Pages
  • Format: Microsoft Word
  • Views: 748
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+234 8130 686 500
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ABSTRACT

This project research aimed to develop a standalone computer application for image classification using Matlab 9.2 by adopting the Rapid Application Development Model (RAD). The software can be used for image preprocessing and image classification. The test run of the software was carried out using acquired LANDSAT image and Google earth image of Federal University of Technology Gidan-Kwano campus. The program was designed to accept the input image in all format for the classification and automatically classified the image by chosen the appropriate method. The outcome of the software was compared with result gotten from the commercial software (ERDAS) and the statistical analysis of the processing time taking for the execution by the two software were affirmed by IBM SPSS software using two ways ANOVA. The outcome of the analysis confirmed that there is no significant different between the classified image by two software using the same method and there is significant different between there time of execution. The ZANNYCLASS 1.0 was able to come to existence by this project research and for efficient and effectiveness of the software its functionality need to be upgraded by further studies.

 

 

                                                                                                                                                

 

 

 

 

 

 

 

 

 

CONTENTS

COVER PAGE

TITLE PAGE

DECLARATION                                                                                                                   i

CERTIFICATION                                                                                                                 ii

DEDICATION                                                                                                                       iii

AKNOWLEDGEMENT                                                                                                        iv

ABSTRACT                                                                                                                           v

TABLE OF CONTENTS                                                                                                       vi

LIST OF TABLES                                                                                                                 xii

LIST OF FIGURES                                                                                                               xiii

CHAPTER ONE                                                                                                                  1

INTRODUCTION                                                                                                                1

1.0 Background to the Study                                                                                                 1

1.1 Statement of Problem                                                                                                       3

1.2 Aim and Objectives of the Study                                                                                     4

1.2.1 Aim                                                                                                                                4

1.2.2 Objective                                                                                                                        4

1.2 Scope of the Project                                                                                                          4

1.4 Study Area                                                                                                                        5

1.5 Limitation                                                                                                                         5

CHAPTER TWO                                                                                                                 6

LITERATURE REVIEW                                                                                                   6

2.0 Theoretical Concept                                                                                                          6

2.1 Supervised                                                                                                                         6

2.1.1 Minimum Distance Algorithm                                                                                       6

2.1.2 K-Nearest Neighbor Algorithm                                                                                     7

2.1.3 Nearest Clustering Algorithm                                                                                        8

2.1.4 Fuzzy C-Means Algorithm                                                                                            8

2.1.5 Maximum Likelihood Algorithm                                                                                   9

2.1.6 Artificial Neural Network Algorithm (ANNs)                                                              10

2.2 Unsupervised                                                                                                                    12

2.2.1 K-Means Clustering Algorithm                                                                                     12

2.2.2    Isodata                                                                                                                                    13

2.3 Software Development Approaches                                                                                 13

2.3.1 Rapid Application Development Model                                                                        14

2.3.2 Spiral Model                                                                                                                  15

2.3.3 Iterative Model                                                                                                              16

2.3.4 Prototype Model                                                                                                                        17

2.3.5 V- Model                                                                                                                       18

2.3.6 Water Fall Model                                                                                                           20

2.3.6 Evolutionary Software Development Model                                                                 21

2.4 Platform Chosen                                                                                                               22

2.5 Image Classification Softwares                                                                                        23

2.5.1 Commercial Softwares                                                                                                   23

2.5.1.1 Idrisi                                                                                                                            23

2.5.1.2 Erdas                                                                                                                           24

2.6 Gap to Be Filled                                                                                                               26

CHAPTER THREE                                                                                                             27

METHODOLOGY                                                                                                               27

3.0 General overview                                                                                                              27

3.1 Requirement Planning                                                                                                       28

3.1.1 System Definition                                                                                                          28

3.1.2 Hardware and Software Used                                                                                       29       

3.1.3 Data Source                                                                                                                   30

3.2 Requirement Definition                                                                                                    30

3.2.1 Unsupervised Classification                                                                                          30

3.2.1.1 Clustering Stage                                                                                                          31

3.3 User Design Phase                                                                                                            32

3.3.1 Flow Chart:                                                                                                                    32

3.3.1.1 Subroutine for software adopted process                                                                   33

3.3.1.2 Subroutine for K-means method                                                                                34

3.3.2 Program Layout Design                                                                                                 35

3.3.3 Designation of Graphical User Interface                                                                       35

3.4 Construction Stage                                                                                                           38

3.5 Implementation of System                                                                                                38

CHAPTER FOUR                                                                                                                40

RESULTS AND DISCUSSION                                                                                          40

4.1 Result Presentation                                                                                                           40

4.1.1 Result of Unsupervised Classification Using Landsat Image                                       40

4.1.1.1 Time Consideration and Processing Speed                                                                 41

4.1.2 Result of Unsupervised Classification Using Google Earth Image                               43

4.1.2.1 Time Consideration and Processing Speed                                                                 44

4.1.3 Comparison of the Outputs with Other Software                                                         45

4.1.3.1 Time Consideration and Processing Speed                                                                 46

4.1.4 Result of Unsupervised Classification Using Google Earth Image                               48

4.2 Result Analysis                                                                                                                 52

4.2.1 The Design                                                                                                                     52

4.2.2 The Data                                                                                                                         52

4.2.3 Hypothesis Testing                                                                                                        52

4.2.4 Statistical Test for the Chosen Hypothesis                                                                    53

4.2.5 Discussion of Results                                                                                                     53

CHAPTER FIVE                                                                                                                 55

SUMMARY, CONCLUSION AND RECOMMENDATIONS                                      55

5.1 Summary                                                                                                                           55

5.2 Conclusion                                                                                                                        56

5.3 Recommendations                                                                                                             56

References                                                                                                                              57

Appendix (Codes)                                                                                                                  61

 

DEVELOPMENT OF A STANDALONE APPLICATION FOR UNSUPERVISED IMAGE CLASSIFICATION
For more Info, call us on
+234 8130 686 500
or
+234 8093 423 853

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  • Type: Project
  • Department: Geography
  • Project ID: GEO0051
  • Access Fee: ₦5,000 ($14)
  • Pages: 102 Pages
  • Format: Microsoft Word
  • Views: 748
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    Details

    Type Project
    Department Geography
    Project ID GEO0051
    Fee ₦5,000 ($14)
    No of Pages 102 Pages
    Format Microsoft Word

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