IRIS BASED MEDICAL ANALYSIS BY GEOMETRIC DEFORMATION FEATURES (original) (raw)
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International Journal of Biomedical Imaging
Iris has specific advantages, which can record all organ conditions, body construction, and psychological disorders. Traces related to the intensity or deviation of organs caused by the disease are recorded systematically and patterned on the iris and its surroundings. The pattern that appears on the iris can be recognized by using image processing techniques. Based on the pattern in the iris image, this paper aims to provide an alternative noninvasive method for the early detection of DM and HC. In this paper, we perform detection based on iris images for two diseases, DM and HC simultaneously, by developing the invariant Haralick feature on quantized images with 256, 128, 64, 32, and 16 gray levels. The feature extraction process does early detection based on iris images. Researchers and scientists have introduced many methods, one of which is the feature extraction of the gray-level co-occurrence matrix (GLCM). Early detection based on the iris is done using the volumetric GLCM d...
Automated Detection of Cholesterol Presence using Iris Recognition Algorithm
International Journal of Computer Applications, 2016
Arcus senilis is a grayish or whitish bow shaped or ring-shaped deposit in the cornea. It is associated with coronary heart disease (CHD). It is also recognized as a sign of hyperlipidemia. Iridology is an alternative medicine to detect diseases using iris's pattern observation. Iridologists believe that the grayish or whitish deposit on the iris is sign of presence of cholesterol or Arcus senilis disease. The simple and non-invasive automation system is developed to detect cholesterol presence using iris recognition algorithm in image processing. This study applies iris recognition method to segment out the iris area, normalization process and lastly determines the cholesterol presence using OTSU's thresholding method and histogram to determine the optimum threshold value. The result showed that the presence of cholesterol was high when the eigenvalue exceeds an optimum threshold value.
Methodology of iris image analysis for clinical diagnosis
2014 International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom), 2014
Healthcare has been a matter of concern for centuries as far as diagnostic techniques for human development are concern. These techniques have been evolving through the ages and human beings have become selective towards cheaper and convenient ones (convenient according to that period of scientific development). But in this selection process we suppress the rare scientific techniques which are no more popular but still exist in our society. This paper is a attempt to collaborate our ancestral knowledge with modern science to make diagnostic techniques more efficient, rapid and user friendly. The main idea is to combine IRIDOLOGY and Image processing with its scientific reasons to open up a new research field and healthcare diagnostic technique. Implementing this method practically requires special image processing where iris feature extraction plays a crucial role. In this paper we study Iridology, a branch of medical science and develop a methodology to implement synergy on image processing with it. This paper will explain the work of image processing of the iris image, the effects of various parameters of algorithm, different image acquisition system specifications, various environments and different sizes of images.
Engineering Journal, 2020
Serious illnesses such as strokes and heart attacks can be triggered by high levels of cholesterol in human blood that exceeds ideal conditions, where the ideal cholesterol level is below 200 mg/dL. To find out cholesterol levels need a long process because the patient must go through a blood sugar test that requires the patient to undergo fasting for 10–12 hours first before the test. Iridology is a branch of science that studies human iris and its relation to the wellness of human internal organs. The method can be used as an alternative for medical analysis. Iridology thus can be used to assess the conditions of organs, body construction, and other psychological conditions. This paper proposes a cholesterol detection system based on the iris image processing using Gray Level Co-Occurrence Matrix (GLCM) and Support Vector Machine (SVM). GLCM is used as the feature extraction method of the image, while SVM acts as the classifier of the features. In addition to GLCM and SVM, this pa...
ON A METHODOLOGY FOR DETECTING DIABETIC PRESENCE FROM IRIS IMAGE ANALYSIS
ris image analysis for clinical diagnosis is one of the most efficient non - invasive diagnosis methods for determining health status of organs. Correc t and timely diagnosis is a critical, yet essential requirement of medical science. From the literature, it is found that modern technology also fails in lot of cases to diagnose disease correctly. The attempt is being made to explore the area of diagnosis from different perspectives. The approach used is a combination of ancestor's technology Iridodiagnosis with modern technology. Iridodiagnosis is an alternative branch of medical science, which can be used for diagnostic purposes. To begin with a database is created of eye images with clinical history of subject’s emphasis on diabetic (type II) disease in pathological laboratory. The various algorithms are developed for image quality assessment, segmentation of iris, iris normalization and clinical feature classification for clinical diagnosis. The Support Vector Machine is used for training and classification purpose. This approach will be useful in the diagnosis field which is faster, user friendly and less time consuming.
2019
Cholesterol is a waxy fat compound that is mostly produced by the liver and the other part is obtained from food. The ideal cholesterol level in the human body is <200. High cholesterol can increase the risk of getting serious diseases such as strokes and heart attacks. Checking cholesterol levels through checking blood sugar requires the patient to undergo fasting for 10-12 hours first and processing the results of the examination also requires not a short time. Because of the seriousness of the disease that can be caused, an early examination is needed and it is also practical to determine the level of excess cholesterol in the human body. Iris has specific advantages which can record all organ conditions, body construction and psychological conditions. Therefore, Iridology as a science based on the arrangement of the iris can be an alternative for medical analysis. In this study, the author designed a system in the matrix simulator which is expected to be able to detect excess...
ipcbee.com
In this paper we propose a new consideration method for cataract diagnosis by considering a statistical texture approach in iris area to improve performance of cataract screening system based on image processing techniques. Statistical texture approach is including average intensity, average contrast, smoothness, third moment, uniformity and entropy. The results show that statistical texture analysis for iris area gave a significant result for serious and non-serious conditions. These results are promising for additional characteristics for getting a robust method for detecting cataract based on image processing.
Design and Implementation Iris Recognition System Using Texture Analysis
Al-Nahrain Journal for Engineering Sciences, 2013
The aim of this work is to produces a technology of recognition and identifies of the person by using the iris. The work was started by reading the images of eyes (UBIRIS database). After that, the iris region localized from the eye image by using the method of image processing. The iris shape is circular so it transfer to rectangular shape and enhance the image and remove the noise like eyelashes and flash of the camera. Then the image quantized from 256 grey levels to 16 grey levels. Four statistical functions used because these functions give us accurate description of iris, the samples had been taken in four angles. The information for each sample is save in database. The last stage is to classify the samples by using neural network. The results will prove that the work have high accurate conclusions.
The Expert System of Cholesterol Detection Based on Iris Using the Gabor Filter
SinkrOn
Cholesterol is a systemic disease. Many complications of its could affect other organs due to uncontrolled cholesterol / fat in the blood. One of them is coronary heart disease. One way to recognize someone having cholesterol is through the eyes. By using the Iridology method, cholesterol disease in a person's body can be detected or seen through the iris of the eye. Checking cholesterol-related conditions is usually done in a hospital or pharmacy. But the problem is that people are still lazy to check their cholesterol. Therefore, we need a software that can make it easier for people to do cholesterol checks. This device will detect cholesterol by using image processing techniques through the iris image accompanied by the Gabor Filter method. From 15 tested data, 13 iris image images were successfully identified, so that the percentage of success of this program was 86%.with 35 trained data.
IJERT-A Review on Feature Extraction Techniques of Iris
International Journal of Engineering Research and Technology (IJERT), 2013
https://www.ijert.org/a-review-on-feature-extraction-techniques-of-iris https://www.ijert.org/research/a-review-on-feature-extraction-techniques-of-iris-IJERTV2IS120972.pdf The biometrics is the study of physical traits or behavioral characteristics of human include items such as finger prints, face, hand geometry, gait, keystrokes, voice and iris. Among the biometrics, iris has highly accurate and reliable characteristics. A general approach of iris recognition system includes image acquisition, segmentation, feature Extraction, matching/classification. The performance of biometric system based on iris recognition depends on the selection of iris features. In this work performance of various feature extraction methods are analyzed for iris recognition. The various methods includes circular symmetric filter, Haar Wavelets, Lifting wavelet transform.