Skin Disease Identification System using Gray Level Co-occurrence Matrix
| Autor: | Noel B. Linsangan, Monica Francesca B. Coching, Joseph Mark G. Aglibut, Jumelyn L. Torres, Luigi L. Alonzo |
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| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
medicine.medical_specialty integumentary system business.industry Human skin 02 engineering and technology Disease medicine.disease Dermatology Identification system Gray level Co-occurrence matrix 020901 industrial engineering & automation Wavelet decomposition Psoriasis 0202 electrical engineering electronic engineering information engineering medicine 020201 artificial intelligence & image processing business Acne |
| Zdroj: | ICCAE |
| DOI: | 10.1145/3057039.3057044 |
| Popis: | Diagnosis of the skin disease has always been in terms of a doctor's knowledgeable opinion, or by number of laboratory screenings. Diagnosis is made by looking for additional signs that make the doctor's statement accurate, however in some cases signs are indistinguishable that results to miss potential diagnosis. With the use of this human skin diseases classification system, diagnosing existing skin disease will be accessible without undergoing laboratory screenings. The skin image is classified using the GLCM (Gray Level Co-Occurrence Matrix) features, wavelet decomposition for normalization, and k-NN (k-nearest neighbors) classifier. The skin disease that will be classified are Acne and Psoriasis. The device was proven to be effective for classifying the skin diseases. Acne have 100% accuracy while Psoriasis have 92% accuracy, with 25 trials per disease. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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