(cache)Recognition of Feline Epidermal Disease using Raspberry-Pi based Gray Level Co-occurrence Matrix and Support Vector Machine | IEEE Conference Publication | IEEE Xplore

Recognition of Feline Epidermal Disease using Raspberry-Pi based Gray Level Co-occurrence Matrix and Support Vector Machine

Publisher: IEEE

Abstract:As of 2018, with over 373 million population of cats worldwide, cases of feline skin diseases have drastically increased as well, with 6-15% of feline patients who have e...View more
Abstract:
As of 2018, with over 373 million population of cats worldwide, cases of feline skin diseases have drastically increased as well, with 6-15% of feline patients who have experienced at least one form of dermatopathy in their lifetimes. Research on detecting feline skin diseases has been focused on using different diagnostic methods in the past. Examples of these methods include the Fur Pluck Method, which uses microscopic hair evaluation to detect parasites. Another study uses Wood’s Lamp method that uses a UV light source to detect dermatophytosis. In this study, the image processing technique in diagnosing two types of skin diseases, Dermatophytosis and Ectoparasitic Skin Disease, was identified using GLCM and SVM to extract the features and classify the images, respectively. The system trained 270 images with 90 photos each on Dermatophytosis, Ectoparasitic, and unknown skin diseases and tested 45 skin disease images. These feline skin disease images used are primarily from Philippine short-haired cats or Puspins. These feline skin disease images used are primarily from domestic short-haired cats. Confusion Matrix was used in determining the accuracy of the system. The accuracy of the system reached 86.776% with 80% on Dermatophytosis Skin Diseases, 93.33% for Ectoparasitic Skin Diseases, and 87% for the Unknown Parameter with 13.224% Error of Commission.
Date of Conference: 28-30 November 2021
Date Added to IEEE Xplore: 16 March 2022
ISBN Information:
Publisher: IEEE
Conference Location: Manila, Philippines
References is not available for this document.

I. Introduction

The skin is the largest part of a cat’s body, and it serves as protection against dangerous environments, a form of temperature control, and gives it tactile sense. The skin comprises 12-24% of the weight of an animal, depending on the specific breed and age of the cat. The epidermis is the outermost layer of animal skin, followed by the dermis, intermediate, and subcutis, the innermost layer. [1]. With the rising population of feline cats worldwide 373 million as of 2018 cases of feline skin diseases have also drastically increased [2]. Studies indicate that 6-15% of feline patients have experienced one form of dermatophytes in their lifetimes, with a significant portion of this number suffering from more than one [3]. Skin Diseases in cats can be classified into two types: Ectoparasitic and Dermatophytosis [4]. Research shows that there is 31.3% overall exposure of cats to ectoparasites [5]. Another study was conducted in one country wherein 37.33% of samples from cats tested positive for dermatophytes [6]. Research on detecting feline skin diseases has been focused on using different diagnostic methods in the past years. For instance, a 2018 study used traditional microscopic methods of parasite detection such as the Fur Pluck (FP) method, which uses a microscopic evaluation of hairs placed in mineral oil on a microscope slide, skin scrapings, skin biopsies, and tape stripping [7]. Another study for detecting dermatophytosis uses the usual room light and examination using the Wood’s Lamp Method [8]. The outcome can sometimes be confirmed in a few days to say that the case is negative of dermatophytosis [9].

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References

References is not available for this document.