Deteksi Level Kolesterol melalui Citra Mata Berbasis HOG dan ANN

ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Pub Date : 2019-05-24 DOI:10.26760/ELKOMIKA.V7I2.284

M. Siddik, Ledya Novamizanti, I. N. Ramatryana

{"title":"Deteksi Level Kolesterol melalui Citra Mata Berbasis HOG dan ANN","authors":"M. Siddik, Ledya Novamizanti, I. N. Ramatryana","doi":"10.26760/ELKOMIKA.V7I2.284","DOIUrl":null,"url":null,"abstract":"ABSTRAKKolesterol merupakan lemak yang berada di dalam darah yang dibutuhkan untuk pembentukan hormon dan sel baru. Kadar kolesterol normal harus kurang dari 200 mg/dL, namun jika di atas 240 mg/dL akan berisiko tinggi terkena penyakit stroke dan jantung koroner. Penelitian ini menghasilkan suatu sistem yang dapat mendeteksi kadar kolesterol seseorang melalui citra mata menggunakan metode iridologi dan image processing. Citra mata diperoleh dari pasien laboratorium klinik sebanyak 120 citra mata. Proses sistem diawali dengan mengolah citra mata dengan metode cropping, resize, dan segmentasi. Metode ekstaksi ciri menggunakan Histogram of Oriented Gradients (HOG), dan klasifikasi menggunakan Artificial Neural Network (ANN). Sistem dapat mendeteksi kadar kolesterol dengan tiga level klasifikasi, yaitu normal, berisiko kolesterol tinggi, dan kolesterol tinggi dengan tingkat akurasi sebesar 93% dan waktu komputasi 0,0862 detik.Kata kunci: citra mata, kadar kolesterol, Histogram of Oriented Gradients, Artificial Neural Network ABSTRACTCholesterol is fat in the blood that is needed for the formation of hormones and new cells. Normal cholesterol levels should be less than 200 mg / dL, but if above 240 mg / dL will be at high risk of stroke and coronary heart disease. This study produced a system that can detect a person's cholesterol levels through eye images using iridology and image processing methods. Eye images obtained from clinical laboratory patients were 120 eye images. The system process begins with processing eye images using the method of cropping, resizing, and segmentation. Feature extraction method uses Histogram of Oriented Gradients (HOG), and classification using Artificial Neural Network (ANN). The system can detect cholesterol levels with three levels of classification, namely normal, at high risk of cholesterol, and high cholesterol with an accuracy rate of 93% and computing time of 0.0862 seconds.Keywords: eye image, cholesterol level, Histogram of Oriented Gradients, Artificial Neural Network","PeriodicalId":344430,"journal":{"name":"ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26760/ELKOMIKA.V7I2.284","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 9

Abstract

ABSTRAKKolesterol merupakan lemak yang berada di dalam darah yang dibutuhkan untuk pembentukan hormon dan sel baru. Kadar kolesterol normal harus kurang dari 200 mg/dL, namun jika di atas 240 mg/dL akan berisiko tinggi terkena penyakit stroke dan jantung koroner. Penelitian ini menghasilkan suatu sistem yang dapat mendeteksi kadar kolesterol seseorang melalui citra mata menggunakan metode iridologi dan image processing. Citra mata diperoleh dari pasien laboratorium klinik sebanyak 120 citra mata. Proses sistem diawali dengan mengolah citra mata dengan metode cropping, resize, dan segmentasi. Metode ekstaksi ciri menggunakan Histogram of Oriented Gradients (HOG), dan klasifikasi menggunakan Artificial Neural Network (ANN). Sistem dapat mendeteksi kadar kolesterol dengan tiga level klasifikasi, yaitu normal, berisiko kolesterol tinggi, dan kolesterol tinggi dengan tingkat akurasi sebesar 93% dan waktu komputasi 0,0862 detik.Kata kunci: citra mata, kadar kolesterol, Histogram of Oriented Gradients, Artificial Neural Network ABSTRACTCholesterol is fat in the blood that is needed for the formation of hormones and new cells. Normal cholesterol levels should be less than 200 mg / dL, but if above 240 mg / dL will be at high risk of stroke and coronary heart disease. This study produced a system that can detect a person's cholesterol levels through eye images using iridology and image processing methods. Eye images obtained from clinical laboratory patients were 120 eye images. The system process begins with processing eye images using the method of cropping, resizing, and segmentation. Feature extraction method uses Histogram of Oriented Gradients (HOG), and classification using Artificial Neural Network (ANN). The system can detect cholesterol levels with three levels of classification, namely normal, at high risk of cholesterol, and high cholesterol with an accuracy rate of 93% and computing time of 0.0862 seconds.Keywords: eye image, cholesterol level, Histogram of Oriented Gradients, Artificial Neural Network

查看原文本刊更多论文

通过猪和安的眼睛图像检测胆固醇水平

胆固醇是存在于血液中的脂肪，用于形成新的激素和细胞。正常胆固醇水平必须低于200毫克/dL，但超过240毫克/dL的几率更高，将导致中风和冠心病。这项研究产生了一种系统，可以通过眼睛图像探测一个人的胆固醇水平，使用iridologi和意象处理器。从临床实验室的病人那里获得了120个眼科图像。系统过程从处理眼睛图像开始，使用倾斜、调整和分割的方法。研究猪方图的外部定义方法，以及人工神经网络(ANN)的分类。该系统可以检测三种分类级别的胆固醇，即正常、高胆固醇风险和高胆固醇水平，准确率为93%，计算时间为0.0862秒。关键词:注重眼睛、胆固醇的直方图Gradients图像,人工神经网络ABSTRACTCholesterol是胖编队》《血就是需要的荷尔蒙和新细胞。正常过高水平应该小于200 mg / dL,但如果240 mg / dL,将头顶at high中风和心脏冠状疾病之风险。这项研究产生了一种系统，可以通过眼睛检测一个人的选择，使用虹膜学和意象处理方法。来自临床实验室的眼科医生证实是120只眼睛。使用倾斜、调整和切削的方法进行的系统处理。用人工神经网络(ANN)进行功能外露。系统可以检测到三层经典的cholesterol水平，namely正常水平，在高震区，高cholesterol值为93%，计算时间为0.0862秒。Keywords:眼象，胆醇水平，东方格式化，人工神经网络

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika

自引率

0.00%

发文量