Skin segmentation using color pixel classification: analysis and comparison

By Son Lam Phung, Abdesselam Bouzerdoum, Douglas Chai. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005

872 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Cell Biology, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/48e04d7ab5e414a20ae2702c387c3322f88bd32b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. Nikolaos G. Bourbakis
2. Praveen K. Kakumanu
3. Sokratis Makrogiannis
4. Miquel Perelló Nieto

In Cell Biology

1. Nikolaos G. Bourbakis
2. Praveen K. Kakumanu
3. Sokratis Makrogiannis
4. Miquel Perelló Nieto

In Computer Vision and Pattern Recognition

1. Nikolaos G. Bourbakis
2. Praveen K. Kakumanu
3. Sokratis Makrogiannis
4. Miquel Perelló Nieto

Citations in the corpus

• A survey of skin-color modeling and detection methods (2007, methodology): “It should be noted that the histogram models were found to be slightly superior to GMMs in terms of skin-pixel classification performance [54,75,76].”
• Merging chrominance and luminance in early, medium, and late fusion using Convolutional Neural Networks (2015, methodology): “Also, YUV has been used in previous works for skin color classification [Chai and Bouzerdoum, 2000] and segmentation [Chai and Ngan, 1999; Phung et al., 2005], facial region location [Chai and Ngan, 1998], and fast image segmentation for interactive robots [Bruce et al.”