Pre-Processing Of Automatic Skin Cancer Detection System: Comparative Study

1S. Maryam, R. Majid, T.K. Lee, M.Stella Atkins, “A novel method for detection of pigment network in dermoscopic images using graphs”, Computerized Medical Imaging and Graphics, 35(2):137-43, 2011.10.1016/j.compmedimag.2010.07.00220724109Search in Google Scholar

2S. Muhamad Isa, M. Eka Suryana, M. Ali Akbar, A. Noviyanto, W. Jatmiko and A. Murni Arymurthy, “Performance Analysis of ECG Signal Compression using SPIHT”, International Journal On Smart Sensing And Intelligent Systems Vol. 6, No. 5, 2013.10.21307/ijssis-2017-624Search in Google Scholar

3Y. LUO, P. LIU, M. LIAO,” An artificial immune network clustering algorithm for mangroves remote sensing image”, International Journal On Smart Sensing And Intelligent Systems Vol. 7, No. 1, 2014.10.21307/ijssis-2017-648Search in Google Scholar

4S. Alina, C. Mihai Ciuc, T. Radulescu, L. Wanyu, D.Petrache, “Preliminary Work on Dermatoscopic Lesion Segmentation,” 20th European Signal Processing Conference (EUSIPCO 2012), August 21-27, Romania, 2012.Search in Google Scholar

5D. Chang, W. Wu, “Image Contrast Enhancement Based on a Histogram Transformation of Local Standard Deviation”, IEEE Transactions on Medical Imaging, Vol. 17, No. 4, 1998.10.1109/42.7303979845308Search in Google Scholar

6K. Madhankuma, and P. Kumar, “Characterization of Skin Lesions”, Proceedings of the International Conference on Pattern Recognition, Informatics and Medical Engineering, March 21-23, India, 201210.1109/ICPRIME.2012.6208362Search in Google Scholar

7M.Sadeghi, M.Razmara, T.K. Lee, M.S. Atkins,” A novel method for detection of pigment network in dermoscopic images using graphs”, Computerized Medical Imaging and Graphics 35, 137–143, 2011.10.1016/j.compmedimag.2010.07.002Search in Google Scholar

8K.A. Norton, H. Iyatomi, M. Emre Celebi, G. Schaefer, M. Tanaka, and K. Ogawa, “Development of a Novel Border Detection Method for Melanocytic and Non-Melanocytic Dermoscopy Images”, 32nd Annual International Conference of the IEEE EMBS Buenos Aires, Argentina, August 31 - September 4, 2010.10.1109/IEMBS.2010.562649921096270Search in Google Scholar

9H.T. Lau, and A. Al-Jumaily, “Automatically Early Detection of Skin Cancer: Study Based on Neural Network Classification”, International Conference of Soft Computing and Pattern Recognition, 4-7 December, Malaysia, 2009.10.1109/SoCPaR.2009.80Search in Google Scholar

10D.H. Chung, G. and Sapiro, “Segmenting Skin Lesions with Partial-Differential-Equations-Based Image Processing Algorithms”, IEEE Transactions on Medical Imaging, Vol. 19, No. 7, 2000.10.1109/42.87520411055791Search in Google Scholar

11A.N. Hoshyar, A. Al-Jumaily, and R. Sulaiman, “Review on Automatic Early Skin Cancer Detection”, International Conference on Computer Science and Service System (CSSS), 27-29 June, China, 2011.Search in Google Scholar

12S.S. Al-amri, N.V. Kalyankar, and S.D. Khamitkar, “Linear and Non-linear Contrast Enhancement Image”, IJCSNS International Journal of Computer Science and Network Security, Vol.10, No.2, pp. 139, 2010.Search in Google Scholar

13S.S. Agaian, K.P. Lentz, and A.M. Grigoryan, “A New Measure of Image Enhancement”, International Conference on Signal Processing & Communication, 5-9 June, 2000.Search in Google Scholar

14L. R. Lagendijk, and J. Biemond, “Basic Methods for Image Restoration and Identification”, Handbook of Image and Video Processing 2nd edition, Elsevier Academic Press, 167-181, 2005.10.1016/B978-012119792-6/50074-7Search in Google Scholar

15R.C. Gonzalez, and R.E. Woods, “Digital Image Processing”, 3rd Edition, Prentice-all, Inc., New Jersey, ISBN: 10: 013168728x, pp: 594, 2008.Search in Google Scholar

16I. Maglogiannis, and C.N. Doukas, “Overview of Advanced Computer Vision Systems for Skin Lesions Characterization”, IEEE Transactions on Information Technology in Biomedicine, Vol. 13, N. 5, 200910.1109/TITB.2009.201752919304487Search in Google Scholar

17M.J. Ogorzaáek, G. Surówka, L. Nowak, and C. Merkwirth, “New Approaches for Computer-Assisted Skin Cancer Diagnosis”, The Third International Symposium on Optimization and Systems Biology (OSB’09), 20-22 September, China, 2009Search in Google Scholar

18J. Mesquita, “Classification of Skin Tumours through the Analysis of Unconstrained Images”, De Montfort University Leicester, Faculty of Computer Science and Engineering, UK, 2008.Search in Google Scholar

19H. Yeganeh, A. Ziaei, A.H. Rezaie, “A Novel Approach for Contrast Enhancement Based on Histogram Equalization”, Proceedings of the International Conference on Computer and Communication Engineering, 13-15 May, Malaysia, 2008.10.1109/ICCCE.2008.4580607Search in Google Scholar

20V.P. Vishwakarma, S. Pandey and M. N. Gupta,” Adaptive Histogram Equalization and Logarithm Transform with Rescaled Low Frequency DCT Coefficients for Illumination Normalization”, International Journal of Recent Trends in Engineering, Vol.1, No. 1, 2009.Search in Google Scholar

21C.W. Kurak, “Adaptive histogram equalization: a parallel implementation”, Proceedings of the Fourth Annual IEEE Symposium in Computer-Based Medical Systems, Univ. of North Florida, Jacksonville, FL, USA,1991.Search in Google Scholar

22X. Xiaoling, and X. Zhang, “An Improved Unsharp Masking Method for Borehole Image Enhancement”, 2nd International Conference on Industrial Mechatronics and Automation,30-31 May, China, 2010.10.1109/ICINDMA.2010.5538297Search in Google Scholar

23D. Prasanna, P.Neelamegam, S.Sriram, N.Raju,” Enhancement of vein patterns in hand image for biometric and biomedical application using various image enhancement techniques”, International Conference On Modeling Optimization And Computing, Procedia Engineering, Vol 38, pp. 1174 – 1185, 2012.Search in Google Scholar

24S.H. Rubin, R. Kountchev, V. Todorov, and R. Kountcheva, “Contrast Enhancement with Histogram-Adaptive Image Segmentation”, IEEE International Conference on Information Reuse and Integration, 16-18 Sep, USA, 2006.10.1109/IRI.2006.252482Search in Google Scholar

25H. Zhang, “Spatially Adaptive Wiener Filtering For Image Denoising Using Undecimated Wavelet Transform”, ELEC 590 project report, Deaprtment of Electrical and Computer Engineering, USA, 1999.Search in Google Scholar

26N. Otsu, “A Threshold Selection Method from Gray Level Histograms,” IEEE Trans SMC, Vol. 9, pp. 62–66, 1979.10.1109/TSMC.1979.4310076Search in Google Scholar

27M.P. Dubuisson, and A.K. Jain, “A modified Hausdorff distance for object matching”, Proceedings of the 12th IAPR International Conference on Computer Vision & Image Processing, Vol. 1, 9-13 Oct, Jerusalem, 1994.Search in Google Scholar

28L. Wang, Y. Zhang, and J. Feng, “On the Euclidean Distance of Images”, Center for Information Sciences, School of Electronics Engineering and Computer Sciences, Peking University, China, 2002.Search in Google Scholar

29S.Varshney, N. Rajpa, and R. Purwar, “Comparative Study of Image Segmentation Techniques and Object Matching using Segmentation”, International Conference on Methods and Models in Computer Science, 14-15 Dec, India, 2009.Search in Google Scholar