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Skin Disease Detection Using Image Processing

Kajal Hanumant Taware, Lekawale Pooja Mahadev, Mandake Utkarsha Uday, Gorad Shurtika Gulab, B. D. Thorat

Abstract


Skin issues incorporate a wide extent of indications and seriousness. They can be pleasant or unsavoury, and they can be momentary or constant. The skin is the human body's largest organ. Between 30 and 70% of people are influenced by the skin related issues. Skin-related health issues affect people all over the world, necessitating quick and effective resolution. As of late, computeraided demonstrative (CAD) innovations have been used to effectively recognize skin cancers in dermatoscopic pictures. Be that as it may, there has been very little inquire about on the foremost common skin infections in clinical pictures taken with cheap cameras or cell phones. To ensure that a CAD system's estimates are reliable, dermatologists must be able to obtain accurate representations of skin damage. We propose viable representations based on dermatological demonstrative criteria to address this issue.


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References


Arivuselvam B. Skin Cancer Detection and Classification Using SVM Classifier. Turkish Journal of Computer and Mathematics Education (TURCOMAT). 2021 Jun 4; 12(13): 1863–71.

ALEnezi NS. A method of skin disease detection using image processing and machine learning.Procedia Comput Sci. 2019 Jan 1; 163: 85–92.

Hasija Y, Garg N, Sourav S. Automated detection of dermatological disorders through imageprocessing and machine learning. In 2017 IEEE International Conference on Intelligent Sustainable Systems (ICISS). 2017 Dec 7; 1047–1051.

Nasiri S, Aslan B, Geller S, Fathi M. A Prototype of Case-Based Skin Cancer Detector for Android Phones Based on DePicT Concept: CBMelanom. In 2016 IEEE International Conference on Computational Science and Computational Intelligence (CSCI). 2016 Dec 15; 98–103.

Ajith A, Goel V, Vazirani P, Roja MM. Digital dermatology: Skin disease detection model using image processing. In 2017 IEEE International Conference on Intelligent Computing and Control Systems (ICICCS) 2017 Jun 15; 168–173.

Sun X, Yang J, Sun M, Wang K. A benchmark for automatic visual classification of clinical skin disease images. In European Conference on Computer Vision. 2016 Oct 8; 206–222. Springer, Cham.

Hay RJ, Johns NE, Williams HC, Bolliger IW, Dellavalle RP, Margolis DJ, Marks R, Naldi L, Weinstock MA, Wulf SK, Michaud C. The global burden of skin disease in 2010: an analysis of the prevalence and impact of skin conditions. J Investig Dermatol. 2014 Jun 1; 134(6): 1527–34.

Spalding JA. The doctor with an inherited defect of colour vision: effect on clinical skills. Br J Gen Pract. 1993 Jan; 43(366): 32–33.

Yang J, Sun X, Liang J, Rosin PL. Clinical skin lesion diagnosis using representations inspired by dermatologist criteria. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018; 1258–1266.

Yadav N, Narang VK, Shrivastava U. Skin diseases detection models using image processing: A survey. Int J Comput Appl. 2016 Mar 17; 137(12): 34–9.

Barata C, Figueiredo MA, Celebi ME, Marques JS. Local features applied to dermoscopy images: Bag-of-features versus sparse coding. In Iberian Conference on Pattern Recognition and Image Analysis. 2017 Jun 20; 528–536. Springer, Cham.

Zhang J, Sclaroff S, Lin Z, Shen X, Price B, Mech R. Minimum barrier salient object detection at

fps. In Proceedings of the IEEE international conference on computer vision. 2015; 1404–1412.

Canny JF. A Variational Approach to Edge Detection. In AAAI Proceedings. 1983 Aug 22; 1983:54–58.

Razeghi O, Qiu G. 2309 skin conditions and crowd-sourced high-level knowledge dataset for building a computer aided diagnosis system. In 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI). 2014 Apr 29; 61–64.

Hamilton AD, Brady RR. Medical professional involvement in smartphone 'apps' in dermatology. Br J Dermatol. 2012 Apr 4; 167(1): 220–1.




DOI: https://doi.org/10.37628/ijippr.v8i1.776

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