Objectionable Image Detection in Cloud Computing Paradigm-a Review

Mustafa, Muhammad

doi:10.3844/jcssp.2013.1715.1721

Cited by 10 publications

(5 citation statements)

References 24 publications

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“…In addition, peer-reviewed scholarship on video pornography filtering was excluded from subsequent analyses. The list of articles in the sample was corroborated with four articles that review the field (Abadpour and Kasaei 2005; Kelly et al 2008; Mustafa and Zhu 2013; Zaidan et al 2013).…”

Section: Methods Of Our Studymentioning

confidence: 93%

Training Computers to See Internet Pornography: Gender and Sexual Discrimination in Computer Vision Science

Gehl

Moyer‐Horner

Yeo

2016

Television & New Media

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This article critically examines computer vision–based pornography filtering (CVPF), a subfield in computer science seeking to train computers on how to recognize the difference between digital pornographic images and nonpornographic images. Based on a review of 102 peer-reviewed CVPF articles, we argue that CVPF has as a whole trained computers to “see” a very specific, idealized form of pornography: pictures of lone, thin, naked women. The article supports this argument by closely reading the algorithms proposed in the CVPF literature and quantitatively analyzing the images included as illustrations of these algorithms. Drawing on pornography studies, we also compare the CVPF pornographic imagination with “noisy” pornography that exceeds computer vision. Ultimately, the article argues that this very narrow imagination of porn in CVPF reflects and reinforces larger gender and sexual inequalities in the technology industry as a whole.

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Section: Methods Of Our Studymentioning

confidence: 93%

Training Computers to See Internet Pornography: Gender and Sexual Discrimination in Computer Vision Science

Gehl

Moyer‐Horner

Yeo

2016

Television & New Media

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“…Some detection of pornographic images called as contour-based and region based [1], and human skin probability [2][3][4] had been performed by some researches. Those methods performed the detection based on the skin information, which were extracted by skin segmentation.…”

Section: Related Workmentioning

confidence: 99%

Pornographic Image Recognition Based on Skin Probability and Eigenporn of Skin ROIs Images

2015

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“…Recent review presented by Mustafa and Zhu (2013) said that most of the works are based on skin color detection, which are not suitable for finding obscenity. The reason for this is that, there are many skins like objects such as beach photos, human skin like animal's fur, skin colored painting that enables false positive and negative rate.…”

Section: Jcsmentioning

confidence: 99%

Fusion of Color and Modified Webers Law Descriptor Based Human Skin Detection

Prema¹

2014

Journal of Computer Science

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Skin detection in images or videos plays a vital role in a wide range of image processing applications like face detection, face tracking, gesture analysis, human-computer interaction etc. Due to its high processing speed and invariant against rotation, it has received significant interest in pattern recognition and computer vision. The robustness of skin detection using color information depends on real world conditions such as background, noise, change of intensity and lightening effects. This situation can be improved by using texture as a descriptor to extract skin pixels in images. This study proposes color based skin detection algorithm (fusion of Cheddad's approach with C r of YC b C r color space) with a texture based skin location algorithm called Modified Weber's Law Descriptions (MWLD) to evaluate region features. MWLD is based on the fact that the Human Visual System (HVS) is more sensitive in lumens contrast than absolute luminance values. In MWLD, the differential excitation and gradient orientation of the current pixel are considered to extract the texture features. For differential excitation, Just Noticeable Distortion (JND) is also used. Due to the absence of red component in Cheddad's new color space for skin detection, the detection rate is not good for real time applications. To improve this situation, the Cr component of YC b C r color space is included to obtain the color features. According to experimental results, the proposed method exhibits satisfactory performance in terms of True Positive Rate (TPR), False Positive Rate (FPR) and Accuracy with wide variations in size, color and orientation. Different window sizes for differential excitation such as 3×3, 5×5 and 7×7 are also taken to check the performance.

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Objectionable Image Detection in Cloud Computing Paradigm-a Review

Cited by 10 publications

References 24 publications

Training Computers to See Internet Pornography: Gender and Sexual Discrimination in Computer Vision Science

Training Computers to See Internet Pornography: Gender and Sexual Discrimination in Computer Vision Science

Pornographic Image Recognition Based on Skin Probability and Eigenporn of Skin ROIs Images

Fusion of Color and Modified Webers Law Descriptor Based Human Skin Detection

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Objectionable Image Detection in Cloud Computing Paradigm-a Review

Cited by 10 publications

References 24 publications

Training Computers to See Internet Pornography: Gender and Sexual Discrimination in Computer Vision Science

Training Computers to See Internet Pornography: Gender and Sexual Discrimination in Computer Vision Science

Pornographic Image Recognition Based on Skin Probability and Eigenporn of Skin ROIs Images

Fusion of Color and Modified Webers Law Descriptor Based Human Skin Detection

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Resources

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Fusion of Color and Modified Webers Law Descriptor Based Human Skin Detection