scholarly journals APLIKASI PENERJEMAH SEBAGAI MEDIA KOMUNIKASI BAGI PENYANDANG DISABILITAS MENGGUNAKAN KOMBINASI METODE SKIN DETECTION-ANFIS, KNN DAN TTS

2021 ◽  
Vol 9 (2) ◽  
pp. 57-64
Author(s):  
Fifin Ayu Mufarroha
Keyword(s):  
Skin Detection

Skin detection in video under uncontrolled illumination

2021 ◽  
Author(s):  
Biplab Ketan Chakraborty ◽  
M. K. Bhuyan ◽  
Karl F. MacDorman
Keyword(s):  
Skin Detection

scholarly journals PKT: fast color-based spatial model for human skin detection

2021 ◽  
Author(s):  
Grace L. Samson ◽  
Joan Lu
Keyword(s):  
Spatial Structure ◽  
Human Skin ◽  
Skin Color ◽  
Skin Detection ◽  
Quad Tree ◽  
Learning Tasks ◽  
Color Detection ◽  
Speed Up ◽  
Image Pixels ◽  
Speed Accuracy

AbstractWe present a new detection method for color-based object detection, which can improve the performance of learning procedures in terms of speed, accuracy, and efficiency, using spatial inference, and algorithm. We applied the model to human skin detection from an image; however, the method can also work for other machine learning tasks involving image pixels. We propose (1) an improved RGB/HSL human skin color threshold to tackle darker human skin color detection problem. (2), we also present a new rule-based fast algorithm (packed k-dimensional tree --- PKT) that depends on an improved spatial structure for human skin/face detection from colored 2D images. We also implemented a novel packed quad-tree (PQT) to speed up the quad-tree performance in terms of indexing. We compared the proposed system to traditional pixel-by-pixel (PBP)/pixel-wise (PW) operation, and quadtree based procedures. The results show that our proposed spatial structure performs better (with a very low false hit rate, very high precision, and accuracy rate) than most state-of-the-art models.

scholarly journals Spatial-based skin detection using discriminative skin-presence features

2014 ◽  
Vol 41 ◽  
pp. 3-13 ◽  
Author(s):  
Michal Kawulok ◽  
Jolanta Kawulok ◽  
Jakub Nalepa
Keyword(s):  
Skin Detection

Optimizing human model reconstruction from RGB-D images based on skin detection

2016 ◽  
Vol 20 (3) ◽  
pp. 159-172 ◽  
Author(s):  
Guang Chen ◽  
Jituo Li ◽  
Jiping Zeng ◽  
Bei Wang ◽  
Guodong Lu
Keyword(s):  
Human Model ◽  
Skin Detection ◽  
Model Reconstruction

Human Skin Detection in Color Images Using Deep Learning

2015 ◽  
Vol 5 (2) ◽  
pp. 1-13 ◽  
Author(s):  
Mohammadreza Hajiarbabi ◽  
Arvin Agah
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Human Skin ◽  
Skin Color ◽  
Color Image ◽  
Gaussian Model ◽  
Color Images ◽  
Skin Detection ◽  
Learning Methods ◽  
Rule Based

Human skin detection is an important and challenging problem in computer vision. Skin detection can be used as the first phase in face detection when using color images. The differences in illumination and ranges of skin colors have made skin detection a challenging task. Gaussian model, rule based methods, and artificial neural networks are methods that have been used for human skin color detection. Deep learning methods are new techniques in learning that have shown improved classification power compared to neural networks. In this paper the authors use deep learning methods in order to enhance the capabilities of skin detection algorithms. Several experiments have been performed using auto encoders and different color spaces. The proposed technique is evaluated compare with other available methods in this domain using two color image databases. The results show that skin detection utilizing deep learning has better results compared to other methods such as rule-based, Gaussian model and feed forward neural network.

scholarly journals Hand Gesture Recognition Using Different Algorithms Based on Artificial Neural Network

2011 ◽  
pp. 128-133
Author(s):  
Shweta K. Yewale ◽  
Pankaj. K. Bharne
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Everyday Life ◽  
Gesture Recognition ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Skin Detection ◽  
Human Beings ◽  
Detection Algorithms ◽  
Machine Interface

Gesture is one of the most natural and expressive ways of communications between human and computer in a real system. We naturally use various gestures to express our own intentions in everyday life. Hand gesture is one of the important methods of non-verbal communication for human beings. Hand gesture recognition based man-machine interface is being developed vigorously in recent years. This paper gives an overview of different methods for recognizing the hand gestures using MATLAB. It also gives the working details of recognition process using Edge detection and Skin detection algorithms.

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