A Comparative Study on Hough Transform Segmentation Approach for Outlier Iris Image

Man, Mustafa; Jabal, Mohamad Faizal Ab; Rahim, Mohd Shafry Mohd

doi:10.1007/978-981-10-0557-2_41

Cited by 3 publications

(7 citation statements)

References 21 publications

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“…The subsequent process is the filtering process where all pixels less than a certain size will be eliminated. The process can be expressed in an arithmetic equation as shown in (12) and (13). The next process is the enhancement on the image.…”

Section: Proposed Approachmentioning

confidence: 99%

“…The system is well accepted and used in the medical field of ophthalmology. This field is concerned with the iris, retina and eyes [12,13,17].…”

Section: Introductionmentioning

confidence: 99%

“…There are multiple Epidemiologic reports that contribute to understanding the risk factors of UM, but the results remain inconsistent [23]. Moreover, the increase of pigment spot size may indicate an eye disease [7,12,13,17]. Observing pigment spot size automatically is also proven to be futile.…”

Section: Introductionmentioning

confidence: 99%

“…Observing pigment spot size automatically is also proven to be futile. In addition, the dynamic form of the pigment spots on the iris surface make it very challenging for them to be detected automatically using the existing iris recognition system [12,13]. The dynamic forms of the pigment spots on the iris surface has been defined as being varied on the shape, the position on the iris surface, and the size.…”

Section: Introductionmentioning

confidence: 99%

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Iris Pigment Spots Detection implementing Thresholding Method

Man,

Jabal,

Rahim

et al. 2018

IJET

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The increment size of the pigment spots on iris surface is indicated to the eye disease. Therefore, an automatic pigment spot detection has been proposed to detect the pigment spots on the iris surface. The main challenge is the type of feature that needs to be used for detection is unidentified. Based on the standard features applied for detection purposes, most of the features, such as shape, edges and vector, are not reliable. This situation occurs because the physical form of the pigment spots on the iris surface are dynamic. Hence, the pigment spots colour is the best feature possible to be applied, because it is moderately consistent. However, the spot colour intensity value are numerous. Several colour intensity values that have been used by other researchers were unable to detect the pigment spots. Henceforth, new colour intensity values based on thresholding method have been proposed in this paper. The approach has been applied through on the HSV colour model. The result shows the proposed values more accurate to detect the spots on the iris surface. The results have been recorded as follows (FAR) 0%, 1.33% and 4%, (FRR) 80%, 73.33%, and 70.67%, (DR) 20%, 25.33% and 25.33%.

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Section: Proposed Approachmentioning

confidence: 99%

“…The system is well accepted and used in the medical field of ophthalmology. This field is concerned with the iris, retina and eyes [12,13,17].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Iris Pigment Spots Detection implementing Thresholding Method

Man,

Jabal,

Rahim

et al. 2018

IJET

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“…These abnormalities may interrupt the recognition process of the iris (Jillela and Ross, 2013). Based on the outlier definition and considering the pigment spots description, this paper has extended the outlier definition to the iris image that contains the pigment spots on the iris surface, which is also possible to interrupt the recognition process (Man et al, 2016). …”

Section: Introductionmentioning

confidence: 99%

Implementation of Geodesic Active Contour Approach for Pigment Spots Segmentation on the Iris Surface

Man

Jabal

Rahim

et al. 2016

Journal of Computer Science

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Abstract:The aim of this paper is to study the effectiveness of geodesic active contour approach to segment the pigment spots on iris surface. Pigment spot is an abnormal marker that appears on the iris surface, which may lead to eye diseases. The multi appearance, scattered location and dynamic shape of the pigment spots on the iris surface make them very difficult to detect using automatic segmentation method. Therefore, this paper presents the preliminary works that observe the efficiency and accuracy of geodesic active contour approach to automatically segment the pigment spots on iris surface. Miles database and "lu_wei_feb_2006" dataset are used in this study. The results of the conducted experiment show that geodesic active contour approach able to correctly and accurately detect up to 77% and 90% of the pigment spots in Miles database and "lu_wei_feb_2006" dataset, respectively.

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