scholarly journals Face detection based on skin color modeling and modified Hausdorff distance

2011 ◽  
Author(s):  
Khalid Mohamed Alajel ◽  
Wei Xiang ◽  
John Leis
Keyword(s):  
Face Detection ◽  
Hausdorff Distance ◽  
Skin Color ◽  
Modified Hausdorff Distance

Automatic Ear Localization Using Entropy-Based Binary Jaya Algorithm and Weighted Hausdorff Distance

2021 ◽  
Vol 12 (1) ◽  
pp. 50-76
Author(s):  
Partha Pratim Sarangi ◽  
Abhimanyu Sahu ◽  
Madhumita Panda ◽  
Bhabani Shankar Prasad Mishra
Keyword(s):  
Hausdorff Distance ◽  
Skin Color ◽  
Template Matching ◽  
Search Space ◽  
Jaya Algorithm ◽  
Illumination Variation ◽  
Skin Segmentation ◽  
Benchmark Datasets ◽  
Edge Based ◽  
Modified Hausdorff Distance

This paper presents an automatic human ear localization technique for handling uncontrolled scenarios such as illumination variation, poor contrast, partial occlusion, pose variation, ear ornaments, and background noise. The authors developed entropy-based binary Jaya algorithm (EBJA) and weighted doubly modified Hausdorff distance (W-MHD) to use edge information rather than pixels intensity values of the side face image. First, it embodies skin segmentation procedure using skin color model and successively remove spurious and non-ear edges which reduces the search space of the skin regions. Secondly, EBJA is proposed to trace dense edge regions as probable ear candidates. Thirdly, this paper developed an edge based weight function to represent the ear shape along with for the edge based template matching using W-MHD to identify true ear from a set of probable ear candidates. Experimental results using publicly available benchmark datasets demonstrate the competitiveness of the proposed technique in comparison to the state-of-the-art methods.

Face detection in single and multiple images using different skin color models

2020 ◽  
Vol 13 ◽  
Author(s):  
Manpreet Kaur ◽  
Jasdev Bhatti ◽  
Mohit Kumar Kakkar ◽  
Arun Upmanyu
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Input Image ◽  
Morphological Operations ◽  
Reliability Model ◽  
Multiple Images ◽  
Face Region ◽  
Bounding Box ◽  
The Face ◽  
Precision And Accuracy

Introduction: Face Detection is used in many different steams like video conferencing, human-computer interface, in face detection, and in the database management of image. Therefore, the aim of our paper is to apply Red Green Blue ( Methods: The morphological operations are performed in the face region to a number of pixels as the proposed parameter to check either an input image contains face region or not. Canny edge detection is also used to show the boundaries of a candidate face region, in the end, the face can be shown detected by using bounding box around the face. Results: The reliability model has also been proposed for detecting the faces in single and multiple images. The results of the experiments reflect that the algorithm been proposed performs very well in each model for detecting the faces in single and multiple images and the reliability model provides the best fit by analyzing the precision and accuracy. Moreover Discussion: The calculated results show that HSV model works best for single faced images whereas YCbCr and TSL models work best for multiple faced images. Also, the evaluated results by this paper provides the better testing strategies that helps to develop new techniques which leads to an increase in research effectiveness. Conclusion: The calculated value of all parameters is helpful for proving that the proposed algorithm has been performed very well in each model for detecting the face by using a bounding box around the face in single as well as multiple images. The precision and accuracy of all three models are analyzed through the reliability model. The comparison calculated in this paper reflects that HSV model works best for single faced images whereas YCbCr and TSL models work best for multiple faced images.

A Novel Approach of Face Detection Based on Skin Color Segmentation and SVM

2011 ◽  
Vol 225-226 ◽  
pp. 437-441
Author(s):  
Jing Zhang ◽  
You Li
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Information Access ◽  
Color Segmentation ◽  
Support Vector ◽  
Svm Classifier ◽  
Novel Approach ◽  
Great Performance ◽  
Face Detection And Recognition ◽  
Detection And Recognition

Nowadays, face detection and recognition have gained importance in security and information access. In this paper, an efficient method of face detection based on skin color segmentation and Support Vector Machine(SVM) is proposed. Firstly, segmenting image using color model to filter candidate faces roughly; And then Eye-analogue segments at a given scale are discovered by finding regions which are darker than their neighborhoods to filter candidate faces farther; at the end, SVM classifier is used to detect face feature in the test image, SVM has great performance in classification task. Our tests in this paper are based on MIT face database. The experimental results demonstrate that the proposed method is encouraging with a successful detection rate.

scholarly journals An Innovative Face Detection Based on YCgCr Color Space

2018 ◽  
Author(s):  
Solly Aryza
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Color Image ◽  
Color Space ◽  
Gaussian Model ◽  
Detection Rates ◽  
Detection Algorithms ◽  
Lighting Conditions ◽  
Wide Range ◽  
Human Faces

It is very challenging to recognize a face from an image due to the wide variety of face and the uncertain of face position. The research on detecting human faces in color image and in video sequence has been attracted with more and more people. In this paper, we propose a novel face detection method that achieves better detection rates. The new face detection algorithms based on skin color model in YCgCr chrominance space. Firstly, we build a skin Gaussian model in Cg-Cr color space. Secondly, a calculation of correlation coefficient is performed between the given template and the candidates. Experimental results demonstrate that our system has achieved high detection rates and low false positives over a wide range of facial variations in color, position and varying lighting conditions.

scholarly journals A Real-Time Face Detection/Tracking Methodology Using Haar-wavelets and Skin Color

2006 ◽  
Vol 13B (3) ◽  
pp. 283-294
Author(s):  
Young-Kyung Park ◽  
Hae-Jong Seo ◽  
Kyoung-Won Min ◽  
Joong-Kyu Kim
Keyword(s):  
Real Time ◽  
Face Detection ◽  
Skin Color ◽  
Haar Wavelets
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