Face recognition under varying illuminations using logarithmic fractal dimension-based complete eight local directional patterns

Faraji, Mohammad Reza; Qi, Xiaojun

doi:10.1016/j.neucom.2016.01.094

Cited by 46 publications

(22 citation statements)

References 57 publications

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“…They propose a Discrete Cosine Transform in the logarithm domain (Chen et al, 2006). Faraji and Qi (2016) suggest other solutions based on logarithmic fractal dimension. Hussain Shah et al (2015) claim that: "Firstly, textural values are changed during illumination normalisation due to increase in the contrast that changes the original pixels of [images].…”

Section: Introductionmentioning

confidence: 95%

“…Analysing images captured with variable lighting conditions is a challenging task that can occur in many settings, such as traffic control (Messelodi et al, 2005;Salti et al, 2015), safety and surveillance (Foresti et al, 2005), underwater vision (Peng and Cosman, 2017;Ancuti et al, 2018), driving assistance (Hautière et al, 2006), face recognition (Chen et al, 2006;Faraji and Qi, 2016;Hussain Shah et al, 2015;Lai et al, 2014), large public health databases of images (Noyel et al, 2017), etc. There is some data in the literature about the difficulties inherent to this issue.…”

Section: Introductionmentioning

confidence: 99%

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Functional Asplund metrics for pattern matching, robust to variable lighting conditions

Noyel

Jourlin

2020

Image Anal Stereol

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In this paper, we propose a complete framework to process images captured under uncontrolled lighting and especially under low lighting. By taking advantage of the Logarithmic Image Processing (LIP) context, we study two novel functional metrics: i) the LIP-multiplicative Asplund metric which is robust to object absorption variations and ii) the LIP-additive Asplund metric which is robust to variations of source intensity or camera exposure-time. We introduce robust to noise versions of these metrics. We demonstrate that the maps of their corresponding distances between an image and a reference template are linked to Mathematical Morphology. This facilitates their implementation. We assess them in various situations with different lightings and movement. Results show that those maps of distances are robust to lighting variations. Importantly, they are efficient to detect patterns in low-contrast images with a template acquired under a different lighting.

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Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Functional Asplund metrics for pattern matching, robust to variable lighting conditions

Noyel

Jourlin

2020

Image Anal Stereol

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“…Due to the changes in lighting conditions, the same face appears differently which decrease the face recognition performance. Even though numbers of illumination normalization methods [44,45] have been proposed, most of them tend to fail under severe illumination variations (e.g., heavy shadows and overexposure) and achieve good performance under constrained conditions. In contrast to these methods, we tend to extract illumination-insensitive feature through DCNN.…”

Section: Related Workmentioning

confidence: 99%

Data augmentation for face recognition

et al. 2017

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“…The watermark signal is generated under key control, typically a binary bit sequence. 7 The watermark signal may contain adaptive information to extract the characteristics of the database; may also contain data owner information, such as trademark logo and copyright text; generally need to be processed before the signal conversion; and then used to generate watermark signal. By extracting the feature of the relational data, and by appropriate transformation processing, the watermark channel is obtained with the participation of the key.…”

Section: Introduction Of Database Watermarking Systemmentioning

confidence: 99%

Research on database watermarking based on Independent Component Analysis and multiple rolling

Cao

Shi

2019

International Journal of Distributed Sensor Networks

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Digital watermarking is an important branch of information hiding technology research field. It is a technology that embeds identifiable data into digital works. In order to protect the copyright of digital products, the basic idea is to embed confidential information in digital products such as images, audio, and video to realize data fusion. The current digital watermarking technology is mainly concentrated in the field of multimedia information (such as images, audio, and video) and made good progress. In this article, based on the large database capacity, and much numerical data characteristics, we proposed a separate component analysis on the database watermarking method. First, this article uses a oneway hash function as the marking algorithm to determine the tuple according to the user's given key, the tuple primary key value, and the tuple scale that needs to be marked. Then the watermark is extracted through the key, and the watermarked information is taken out in the database. The matrix is separated by the ratio Independent Component Analysis algorithm, and the watermark is used to separate the matrix. This kind of watermark information is rolled up, and the information in the original database is kept independent of each other, and the embedded watermark information is changed by the smaller carrier. The Independent Component Analysis method is used to extract the watermark image, and the ratio Independent Component Analysis method is used to solve the problem of the influence of the uncertainty of the arrangement order. The experimental results show that the proposed method has a good detection effect.

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Face recognition under varying illuminations using logarithmic fractal dimension-based complete eight local directional patterns

Cited by 46 publications

References 57 publications

Functional Asplund metrics for pattern matching, robust to variable lighting conditions

Functional Asplund metrics for pattern matching, robust to variable lighting conditions

Data augmentation for face recognition

Research on database watermarking based on Independent Component Analysis and multiple rolling

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