Optimal and simultaneous designs of Hermitian transforms and masks for reducing intraclass separations of feature vectors for anomaly detection of diabetic retinopathy images

S. R. Subramaniam*, A. Georgakis, B. W K Ling, J. Goh, H. L. Tang, T. Peto, G. Saleh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes a novel methodology for the optimal and simultaneous designs of both Hermitian transforms and masks for reducing the intraclass separations of feature vectors for anomaly detection of diabetic retinopathy images. Each class of training images associates with a Hermitian transform, a mask and a known represented feature vector. The optimal and simultaneous designs of both the Hermitian transforms and the masks are formulated as least squares optimization problems subject to the Hermitian constraints. Since the optimal mask of each class of training images is dependent on the corresponding optimal Hermitian transform, only the Hermitian transforms are required to be designed. Nevertheless, the Hermitian transform design problems are optimization problems with highly nonlinear objective functions subject to the complex valued quadratic Hermitian constraints. This kind of optimization problems is very difficult to solve. To address the difficulty, this paper proposes a singular value decomposition approach for deriving a condition on the solutions of the optimization problems as well as an iterative approach for solving the optimization problems. Since the matrices characterizing the discrete Fourier transform, discrete cosine transform and discrete fractional Fourier transform are Hermitian, the Hermitian transforms designed by our proposed approach are more general than existing transforms. After both the Hermitian transforms and the masks for all classes of training images are designed, they are applied to test images. The test images will assign to the classes where the Euclidean 2-norms of the differences between the processed feature vectors of the test images and the corresponding represented feature vectors are minimum. Computer numerical simulation results show that the proposed methodology for the optimal and simultaneous designs of both the Hermitian transforms and the masks is very efficient and effective. The proposed technique is also very efficient and effective for reducing the intraclass separations of feature vectors for anomaly detection of diabetic retinopathy images.

Original languageEnglish
Title of host publicationProceedings of the 2012 8th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2012
DOIs
Publication statusPublished - 12 Nov 2012
Externally publishedYes
Event2012 8th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2012 - Poznan, Poland
Duration: 18 Jul 201220 Jul 2012

Conference

Conference2012 8th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2012
CountryPoland
CityPoznan
Period18/07/201220/07/2012

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

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    Subramaniam, S. R., Georgakis, A., Ling, B. W. K., Goh, J., Tang, H. L., Peto, T., & Saleh, G. (2012). Optimal and simultaneous designs of Hermitian transforms and masks for reducing intraclass separations of feature vectors for anomaly detection of diabetic retinopathy images. In Proceedings of the 2012 8th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2012 [6292734] https://doi.org/10.1109/CSNDSP.2012.6292734