HOS image similarity measure for human face recognition

Shnain, Noor Abdalrazak; Lu, Shan; Hussain, Zahir M.

doi:10.1109/compcomm.2017.8322814

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…kurtosis and skewness measure (KSDM) is a measure for image similarity introduced by (Shnain, Hussain et al, 2017). KSM is based on highorder statistics (HOS).…”

Section: Related Workmentioning

confidence: 99%

Design of a hybrid measure for image similarity: a statistical, algebraic, and information-theoretic approach

Al-Janabi

Hussain

Shnain

et al. 2019

European Journal of Remote Sensing

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Image similarity or distortion assessment is fundamental to a wide range of applications throughout the field of image processing and computer vision. Many image similarity measures have been proposed to treat specific types of image distortions. Most of these measures are based on statistical approaches, such as the classic SSIM. In this paper, we present a different approach by interpolating the information theory with the statistic, because the information theory has a high capability to predict the relationship among image intensity values. Our unique hybrid approach incorporates information theory (Shannon entropy) with a statistic (SSIM), as well as a distinctive structural feature provided by edge detection (Canny). Correlative and algebraic structures have also been utilized. This approach combines the best features of Shannon entropy and a joint histogram of the two images under test, and SSIM with edge detection as a structural feature. The proposed method (ISSM) has been tested versus SSIM and FSIM under Gaussian noise, where good results have been obtained even under a wide range of PSNR. Simulation results using the IVC and TID2008 image databases show that the proposed approach outperforms the SSIM and FSIM approaches in similarity and recognition of the image. ARTICLE HISTORY

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“…kurtosis and skewness measure (KSDM) is a measure for image similarity introduced by (Shnain, Hussain et al, 2017). KSM is based on highorder statistics (HOS).…”

Section: Related Workmentioning

confidence: 99%

Design of a hybrid measure for image similarity: a statistical, algebraic, and information-theoretic approach

Al-Janabi

Hussain

Shnain

et al. 2019

European Journal of Remote Sensing

Self Cite

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show abstract

“…Face recognition is falling within the similarity of images where it is possible to recognize the face by finding the similarity and dissimilarity between the image stored in the database and the current image of the same person [3,4]. There are different approaches for face recognition, especially statistical and information-theoretic.…”

Section: Introductionmentioning

confidence: 99%

An Entropy-Histogram Approach for Image Similarity and Face Recognition

Al-Janabi

Hussain

2018

Mathematical Problems in Engineering

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Image similarity and image recognition are modern and rapidly growing technologies because of their wide use in the field of digital image processing. It is possible to recognize the face image of a specific person by finding the similarity between the images of the same person face and this is what we will address in detail in this paper. In this paper, we designed two new measures for image similarity and image recognition simultaneously. The proposed measures are based mainly on a combination of information theory and joint histogram. Information theory has a high capability to predict the relationship between image intensity values. The joint histogram is based mainly on selecting a set of local pixel features to construct a multidimensional histogram. The proposed approach incorporates the concepts of entropy and a modified 1D version of the 2D joint histogram of the two images under test. Two entropy measures were considered, Shannon and Renyi, giving a rise to two joint histogram-based, information-theoretic similarity measures: SHS and RSM. The proposed methods have been tested against powerful Zernike-moments approach with Euclidean and Minkowski distance metrics for image recognition and well-known statistical approaches for image similarity such as structural similarity index measure (SSIM), feature similarity index measure (FSIM) and feature-based structural measure (FSM). A comparison with a recent information-theoretic measure (ISSIM) has also been considered. A measure of recognition confidence is introduced in this work based on similarity distance between the best match and the second-best match in the face database during the face recognition process. Simulation results using AT&T and FEI face databases show that the proposed approaches outperform existing image recognition methods in terms of recognition confidence. TID2008 and IVC image databases show that SHS and RSM outperform existing similarity methods in terms of similarity confidence.

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Toilet Floor Trash Detection System for Unidentified Solid Waste

Wiyagi,

Wada

2024

JRM

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The maintenance of public toilets, such as those found in convenience stores, presents challenges in the era of limited human resources. Consequently, the development of an automatic toilet cleaning system is necessary. The detection of trash on the toilet floor is an essential component of the automatic toilet cleaning system. However, this process presents its own set of challenges, including the unpredictability of the types and locations of the trash that may be present. This study proposes a system for detecting solid waste on the toilet floor by applying the structure and feature similarity index method of image. The difference in the structure and features of the reference and actual images can indicate the trash that appears on the toilet floor. This study also proposes a method for determining the threshold value of similarity feature measurement. The experimental results demonstrate that the proposed detection system is able to produce a detection success rate of up to 96.5%. Additionally, the system proves capable of detecting small objects, such as human hair, under specific conditions. This method offers a resource-efficient solution to the challenges faced in maintaining public toilet cleanliness.

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HOS image similarity measure for human face recognition

Cited by 4 publications

References 18 publications

Design of a hybrid measure for image similarity: a statistical, algebraic, and information-theoretic approach

Design of a hybrid measure for image similarity: a statistical, algebraic, and information-theoretic approach

An Entropy-Histogram Approach for Image Similarity and Face Recognition

Toilet Floor Trash Detection System for Unidentified Solid Waste

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