Skin color and feature-based face detection in complicated backgrounds

2011 ◽  
Author(s):  
YuanHui Wang ◽  
LiQian Xia
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Feature Based

scholarly journals An Optimal MSER Descriptor Based Facial Expression Recognition System using Artificial Intelligence Method

2020 ◽  
Vol 9 (3) ◽  
pp. 3571-3574
Keyword(s):  
Artificial Intelligence ◽  
Face Detection ◽  
Skin Color ◽  
Recognition System ◽  
Expression Recognition ◽  
Binary Images ◽  
Knowledge Based ◽  
Average Accuracy ◽  
Feature Based ◽  
Image Computation

In this Artificial intelligence based Facial emotion recognition system (AI_FERS) model, emotions of facial expressions through performing some predefined steps such as face acquisition, pre-processing of images, face detection, feature extraction & classification have recognized. In the pre-processing of the image phase include the approaches used for face detection is: Knowledge-based, Feature-based, Template-based, and Appearance-based approach. Binary image computation, Skin-color segmentation and morphological filtering, which includes the dilation of Binary images and Gray Images are being extensively applied. For features extraction from images MSER (Maximally Stable External Regions) technique is used. At the final step categorize of emotion into six parts: surprise, fear, disgust, anger, happiness, and sadness come as an outcome using ANN (Artificial Neural Network) technique. The efficiency of the system is examined based on performance parameters such as FAR, FRR, accuracy and execution time. The average accuracy of the AI_FERS model examined is about 98.23 %.

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.

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