2011
DOI: 10.1109/tce.2011.5955203
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A practical system for detecting obscene videos

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Cited by 14 publications
(18 citation statements)
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“…Also, the use of voting algorithm without the extraction of key frames makes the algorithm unsuitable for the classification of small video episodes with different categories. The algorithm of [15] also used spatial features based on Zernike moments to detect nudity in the video file. The approaches used the global motion in the video frames to group frames and reduce the processing time.…”
Section: Methodsmentioning
confidence: 99%
“…Also, the use of voting algorithm without the extraction of key frames makes the algorithm unsuitable for the classification of small video episodes with different categories. The algorithm of [15] also used spatial features based on Zernike moments to detect nudity in the video file. The approaches used the global motion in the video frames to group frames and reduce the processing time.…”
Section: Methodsmentioning
confidence: 99%
“…Furthermore, compared to homogeneous textures such as bricks or sands which have the uniform statistical features, inhomogeneous textures like clouds or flowers generally cannot be extracted robust texture features using conventional algorithms focusing on homogeneous textures [25]. In effectively making up the missed shape and space information of the holistic texture image when LBP texture features are extracted, Zernike moment is a desirable choice.…”
Section: Introductionmentioning
confidence: 99%
“…Moments and functions of moments have been successfully utilized as pattern features in many applications such as image recognition [26] and image retrieval [25] which can capture global information of the image. Zernike moments are deduced based on the theory of orthogonal polynomials.…”
Section: Introductionmentioning
confidence: 99%
“…Modeling the skin colour of humanbeings is very challenging task in image analysis since it is influenced by various factors such as illumination, camera characteristics, ethnicity, individual characteristics, subject appearance, background colour, shadow and motion etc., [2] [3].…”
Section: Introductionmentioning
confidence: 99%
“…Kakhamanu et al [28] have reviewed the methods for skin colour modeling and detection. Chang-Yul Kim et al [3] studied a practical system for detecting obscene videos. Ki-won Byun and Ki-Gon Nam [29] studied the skin region detection using mean shift algorithm based on the histogram approximation.…”
Section: Introductionmentioning
confidence: 99%