Retracted: Preliminary study on iris recognition system: Tissues of body organs in iridology

Othman, Zuraini; Prabuwono, Anton Satria

doi:10.1109/iecbes.2010.5742211

Cited by 17 publications

(12 citation statements)

References 13 publications

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“…Depending upon the health of individual, certain changes like holes, fractures, hyperpigmentations, radii solaris, nerve rings, lines, and color of iris [2,3,5] are observed in the iris texture. Many researchers have proposed large number of algorithms such as Gabor filters [12,13], Hilbert transform [17], wavelet transform [21][22][23], and cumulative SUM-based change analysis [24] for iris recognition system.…”

Section: Feature Extractionmentioning

confidence: 99%

“…The pancreas is a fish-shaped, grayish pink gland about 5 in long that stretches across back of the abdomen behind the stomach. Several researchers [1][2][3][4][5][6][7] have utilized iris recognition system along with clinical iridology as an aid to doctors in making their decision. Accuracy of various iridology-based diagnostic models is being illustrated in Table 1.…”

Section: Introductionmentioning

confidence: 99%

“…Iris recognition system can also be used for clinical applications. A large number of researchers [1][2][3][4][5][6][7] have utilized iris recognition algorithms along with iridology to determine the status of the health of an individual. Iridology, referred to as iris diagnosis [7,8], is an alternate medicine technique through which colors, patterns, and characteristics of iris can be used to gather the information regarding the status of health of an individual.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Determining diabetes using iris recognition system

Bansal

Agarwal

Sharma

2015

Int J Diabetes Dev Ctries

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Iridology is a science which correlates the apparitions of iris to tissue weaknesses in the body. It merely reveals weaknesses, inflammation, or toxicity in organs or tissues. It also indicates weakness long before the symptoms appear. In this paper, support vector machine-based iris recognition system utilizing iridology has been used to determine diabetes. Features from eye image database of 40 people having healthy eye (normal) and having affected eye (diabetes) have been extracted by 2-D wavelet tree. The overall accuracy is obtained to be 87.50 % which reasonably demonstrates the effectiveness of the system.

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Section: Feature Extractionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Determining diabetes using iris recognition system

Bansal

Agarwal

Sharma

2015

Int J Diabetes Dev Ctries

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“…Pengenalan pola iris memberikan banyak manfaat bagi mereka yang mempraktikkan iridologi untuk mendeteksi gejala berdasarkan pola di iris pasien. Dalam iridologi, ada banyak faktor di dalamnya analisis iris harus dipertimbangkan karena struktur iris yang rumit (Othman, 2010…”

Section: Metode Penelitian Iridologiunclassified

Identifikasi Pola Penyakit Pada Citra Iris Mata dengan RBF Neural Network

2018

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AbstrakGaya kehidupan manusia semakin beragam dan padat sehingga banyak terjadi dimana penyakit dan gangguan pada tubuh diketahui ketika sudah dalam kondisi parah. Kebanyakan manusia tidak disiplin dalam memantau kesehatan mereka karena dirasa belum ada cara yang mudah dan efisien, cara yang mayoritas digunakan adalah check-up ke rumah sakit. Iris mata manusia dapat menjadi salah satu media atau sarana dalam mengenali gangguan kondisi tubuh seseorang. Pola yang muncul pada iris mata dapat dikenali dengan bantuan teknologi jaringan saraf tiruan yang salah satunya adalah metode RBF yang dipakai dalam penelitian ini. Hasil yang ditemui pada penelitian ini adalah penggunaan metode RBF mampu untuk mengenali pola yang ada di iris mata, dan dapat memberikan hasil pengenalan penyakit kompleks dan stress dengan akurasi yang dibilang masih rata-rata (sekitar 50%). Kata Kunci: Penyakit, Iris Mata, Pola, RBF AbstractHuman lifestyle is more diverse and dense, so much happening where disease and disturbance in the body are known when it is in severe condition. Most humans are not disciplined in monitoring their health because it feels there is no easy and efficient way, the way that the majority used is the check-up to the hospital. The iris of the human eye can be one of the media or means in recognizing a person's body condition disorder. Patterns that appear on the iris can be identified with the help of artificial neural network technology one of which is the RBF method used in this study. The results found in this study are the use of RBF method to recognize the existing pattern in the iris and can provide the results of the introduction of complex diseases and stress with an accuracy that is still fairly average (about 50%). Keywords: Disease, Eye Iris, Pattern, RBF

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“…Besides the biometric identification, iris textures and colors are related to the healthiness of the internal organs of a person. The place of the iris is near the human nervous system, and after examining the iris, it can reveal significant information about the human health imbalance and nature of possible disturbances in internal body organs, which is called iris diagnosis (iridology) [2,4]. Additionally, extensive research has shown that the human iris can be used as a manifestation of health status [2,3].…”

Section: Introductionmentioning

confidence: 99%

Classification of Body Constitution Based on TCM Philosophy and Deep Learning

Aslam

Yang

et al. 2020

Symmetry

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There is a growing demand for alternative or complementary medicine in health care disciplines that uses a non-invasive instrument to evaluate the health status of various organs inside the human body. In this regard, we proposed a real-time, non-invasive, and painless technique to assess an individual’s health condition. Our approach is based on the combination of iridology and the philosophy of traditional Chinese medicine (TCM). The iridology chart presents perfect symmetry between the left and right eyes, and such a unique representation reveals the body constitution based on TCM philosophy, which classifies the aforementioned body constitution into a combination of nine categories to describe the varieties of genomic traits. In addition, we applied a deep-learning method along with the combination of iridology and TCM to predict the possible physiological or psychological strength or weakness of the subjects and give advice to them about how to take care of their health according to the body constitution assessment. We used several pre-trained convolutional neural networks (CNNs, or ConvNet), such as a residual neural network (ResNet50), InceptionV3, and dense convolutional network (DenseNet201), to classify the body constitution using iris images. In the experiments, the CASIA-Iris-Thousand database was used to perform this task. The experimental results showed that the proposed iris-based health assessment method achieved an 82.9% accuracy.

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Retracted: Preliminary study on iris recognition system: Tissues of body organs in iridology

Cited by 17 publications

References 13 publications

Determining diabetes using iris recognition system

Determining diabetes using iris recognition system

Identifikasi Pola Penyakit Pada Citra Iris Mata dengan RBF Neural Network

Classification of Body Constitution Based on TCM Philosophy and Deep Learning

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