Astatistical performance in dicator in some image processing problems / Chang Yun Fah
The ability to compare or relate two digital images may be useful in developing performance evaluation algorithms. This thesis investigates the use of a particular correlation measure, 2 p R developed from the multidimensional unreplicated linear functional relationship (MULFR) model with single...
| _version_ | 1848773099940478976 |
|---|---|
| author | Chang, Yun Fah |
| author_facet | Chang, Yun Fah |
| author_sort | Chang, Yun Fah |
| building | UM Research Repository |
| collection | Online Access |
| description | The ability to compare or relate two digital images may be useful in developing
performance evaluation algorithms. This thesis investigates the use of a particular
correlation measure, 2
p R developed from the multidimensional unreplicated linear
functional relationship (MULFR) model with single slope, as a measure or indicator of
performance. This MULFR model is an extended version of the ULFR model
introduced by Adcock in 1877. A literature survey was carried out showing that 2
p R has
not been used before. The coefficient 2
p R was investigated in its ability to handle the
issues of non-perfect reference image, multiple image attributes and combining image
local-global information simultaneously. This survey is followed with the maximum
likelihood estimation of parameters and a brief discussion of some theoretical properties
of 2
p R . To investigate robust properties of 2
p R , an extensive simulation exercise was
then carried out. Promising results, thus far, motivate the use of 2
p R in two image
analysis problems; firstly a character recognition problem and secondly a particular data
compression problem. In a handwritten Chinese character recognition problem, the 2
p R
achieved the highest recognition rates even the pre-processing stage is removed from
the recognition system. A substantial reduction of processing time, approximately
40.36% to 75.31%, was achieved using 2
p R . In JPEG compression problem, 2
p R is used
as a measure of image quality which in turn indicates the performance of the
compression method. It is shown that 2
p R performs well and satisfies the monotonicity,
accuracy and consistency properties when perfect reference image was used. 2
p R was
also shown to perform better than some frequently used similarity measures when
imperfect reference image was used. |
| first_indexed | 2025-11-14T13:37:02Z |
| format | Thesis |
| id | um-6201 |
| institution | University Malaya |
| institution_category | Local University |
| last_indexed | 2025-11-14T13:37:02Z |
| publishDate | 2012 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | um-62012016-03-19T01:32:19Z Astatistical performance in dicator in some image processing problems / Chang Yun Fah Chang, Yun Fah Q Science (General) The ability to compare or relate two digital images may be useful in developing performance evaluation algorithms. This thesis investigates the use of a particular correlation measure, 2 p R developed from the multidimensional unreplicated linear functional relationship (MULFR) model with single slope, as a measure or indicator of performance. This MULFR model is an extended version of the ULFR model introduced by Adcock in 1877. A literature survey was carried out showing that 2 p R has not been used before. The coefficient 2 p R was investigated in its ability to handle the issues of non-perfect reference image, multiple image attributes and combining image local-global information simultaneously. This survey is followed with the maximum likelihood estimation of parameters and a brief discussion of some theoretical properties of 2 p R . To investigate robust properties of 2 p R , an extensive simulation exercise was then carried out. Promising results, thus far, motivate the use of 2 p R in two image analysis problems; firstly a character recognition problem and secondly a particular data compression problem. In a handwritten Chinese character recognition problem, the 2 p R achieved the highest recognition rates even the pre-processing stage is removed from the recognition system. A substantial reduction of processing time, approximately 40.36% to 75.31%, was achieved using 2 p R . In JPEG compression problem, 2 p R is used as a measure of image quality which in turn indicates the performance of the compression method. It is shown that 2 p R performs well and satisfies the monotonicity, accuracy and consistency properties when perfect reference image was used. 2 p R was also shown to perform better than some frequently used similarity measures when imperfect reference image was used. 2012 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/6201/1/1_Front_Cover_[ChangYF1].pdf application/pdf http://studentsrepo.um.edu.my/6201/2/2_Preface[ChangYF1].pdf application/pdf http://studentsrepo.um.edu.my/6201/3/3_Chapter_1_Introduction_[ChangYF1].pdf application/pdf http://studentsrepo.um.edu.my/6201/4/4_Chapter_2_Literature_Survey_[ChangYF1].pdf application/pdf http://studentsrepo.um.edu.my/6201/5/5_Chapter_3_ULFR_[ChangYF1].pdf application/pdf http://studentsrepo.um.edu.my/6201/6/6_Chapter_4_MULFR_[ChangYF1].pdf application/pdf http://studentsrepo.um.edu.my/6201/7/7_Chapter_5_Simulation_Study_[ChangYF1].pdf application/pdf http://studentsrepo.um.edu.my/6201/8/8_Chapter_6_Online_HCCR_[ChangYF1].pdf application/pdf http://studentsrepo.um.edu.my/6201/9/9_Chapter_7_JPEG_Image_Quality_Assessment_[ChangYF1].pdf application/pdf http://studentsrepo.um.edu.my/6201/10/10_Chapter_8_Conclusion_[ChangYF1].pdf application/pdf http://studentsrepo.um.edu.my/6201/11/11_References_[ChangYF1].pdf application/pdf http://studentsrepo.um.edu.my/6201/12/12_Appendix_[ChangYF1].pdf application/pdf http://studentsrepo.um.edu.my/6201/13/Page_2_Declaration_Form.pdf Chang, Yun Fah (2012) Astatistical performance in dicator in some image processing problems / Chang Yun Fah. PhD thesis, University of Malaya. http://studentsrepo.um.edu.my/6201/ |
| spellingShingle | Q Science (General) Chang, Yun Fah Astatistical performance in dicator in some image processing problems / Chang Yun Fah |
| title | Astatistical performance in dicator in some image processing problems / Chang Yun Fah |
| title_full | Astatistical performance in dicator in some image processing problems / Chang Yun Fah |
| title_fullStr | Astatistical performance in dicator in some image processing problems / Chang Yun Fah |
| title_full_unstemmed | Astatistical performance in dicator in some image processing problems / Chang Yun Fah |
| title_short | Astatistical performance in dicator in some image processing problems / Chang Yun Fah |
| title_sort | astatistical performance in dicator in some image processing problems / chang yun fah |
| topic | Q Science (General) |
| url | http://studentsrepo.um.edu.my/6201/ http://studentsrepo.um.edu.my/6201/1/1_Front_Cover_[ChangYF1].pdf http://studentsrepo.um.edu.my/6201/2/2_Preface[ChangYF1].pdf http://studentsrepo.um.edu.my/6201/3/3_Chapter_1_Introduction_[ChangYF1].pdf http://studentsrepo.um.edu.my/6201/4/4_Chapter_2_Literature_Survey_[ChangYF1].pdf http://studentsrepo.um.edu.my/6201/5/5_Chapter_3_ULFR_[ChangYF1].pdf http://studentsrepo.um.edu.my/6201/6/6_Chapter_4_MULFR_[ChangYF1].pdf http://studentsrepo.um.edu.my/6201/7/7_Chapter_5_Simulation_Study_[ChangYF1].pdf http://studentsrepo.um.edu.my/6201/8/8_Chapter_6_Online_HCCR_[ChangYF1].pdf http://studentsrepo.um.edu.my/6201/9/9_Chapter_7_JPEG_Image_Quality_Assessment_[ChangYF1].pdf http://studentsrepo.um.edu.my/6201/10/10_Chapter_8_Conclusion_[ChangYF1].pdf http://studentsrepo.um.edu.my/6201/11/11_References_[ChangYF1].pdf http://studentsrepo.um.edu.my/6201/12/12_Appendix_[ChangYF1].pdf http://studentsrepo.um.edu.my/6201/13/Page_2_Declaration_Form.pdf |