A low lighting or contrast ratio visible iris recognition using iso-contrast limited adaptive histogram equalization

Raffei, Anis Farihan Mat; Asmuni, Hishammuddin; Hassan, Rohayanti; Othman, Razib M.

doi:10.1016/j.knosys.2014.11.002

Cited by 33 publications

(21 citation statements)

References 22 publications

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“…This approach generates a saliency map followed by morphological opening and applied contrast limited adaptive histogram equalization (CLAHE) technique. This approach results with less false edges and restore the color in a normal scene [3] .…”

Section: Literature Reviewmentioning

confidence: 97%

Enhancing Visibility Range in Foggy Weather by Contrast Stretched CLAHE (CS- CLAHE)

Jain¹,

Nirvikar²

2019

IJITEE

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Road accidents are becoming a very common problem due to unfavorable weather conditions like rain, fog, and pollution etc. The reason behind such accident is due to poor visibility outside, on the roads and hence driving becomes a problematic issue. Poor visibility becomes due to atmospheric trend originated such as fog, mist originated by small particles in the air such as dust, smoke or moisture, which reduces the visibility of the outdoor scenes. In this paper we are suggesting a Contrast Stretched CLAHE (CS-CLAHE) which will enhance the visibility of outside environment to take necessary precautions for prevention and avoiding the accidents. In the situation of real time streaming, there is a sequence of multiple frames per second, which are to be processed for enhancing the streaming. Therefore, this paper will discuss as a first step: how to enhance a single image and at second stage, processing of multiple images of streaming in parallel processing environment. For fast processing FPGA model is suggested.

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Section: Literature Reviewmentioning

confidence: 97%

Enhancing Visibility Range in Foggy Weather by Contrast Stretched CLAHE (CS- CLAHE)

Jain¹,

Nirvikar²

2019

IJITEE

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“…The iris recognition technology determines the identity of an individual through many steps, as shown in Fig. 1 [48,49]. These steps of iris recognition are as follows:…”

Section: Iris Recognitionmentioning

confidence: 99%

Efficient Biometric Iris Recognition Based on Iris Localization Approach

Al-Ani

2019

UHD J SCI TECH

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Biometric recognition is an emerging technology that has attracted more attention in recent years. This issue uses physiological and behavioral characteristics to identify an individual. The iris recognition approaches are among the most accurate biometric technologies with immense potential for use in global security applications. The purpose of this research is to implement an efficient approach to treat the diseased eye images in order to verify the second iris examination for the same person by inserting an improvement step to the iris recognition system. This step makes a correction of boundary around pupil and removes fraction regions. This approach demonstrates its ability to detect the inner limit of the iris. The obtained results shows that 90% success in the detection diseased eye images, which makes the iris recognition system more accurate and safe.

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“…CLAHE splits the images into different blocks and applies adaptive histogram equalization. Hence, this method stretches color distribution of an image using the most frequent intensity values [34,37], and yields a contrast improved image. In CLAHE two key parameters viz.…”

Section: Preprocessingmentioning

confidence: 99%

Local configuration pattern features for age-related macular degeneration characterization and classification

Mookiah

Acharya

Fujita

et al. 2015

Computers in Biology and Medicine

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A low lighting or contrast ratio visible iris recognition using iso-contrast limited adaptive histogram equalization

Cited by 33 publications

References 22 publications

Enhancing Visibility Range in Foggy Weather by Contrast Stretched CLAHE (CS- CLAHE)

Enhancing Visibility Range in Foggy Weather by Contrast Stretched CLAHE (CS- CLAHE)

Efficient Biometric Iris Recognition Based on Iris Localization Approach

Local configuration pattern features for age-related macular degeneration characterization and classification

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