A Face Detection Method Based on Skin Color Model and Improved AdaBoost Algorithm

This paper integrates skin color model and improved AdaBoost into a face detection method for high-resolution images with complex backgrounds. Firstly, the skin color areas were detected in a multi-color space. Each image was subject to adaptive brightness compensation, and converted into the YCbCr space, and a skin color model was established to solve face similarity. After eliminating the background interference by morphological method, the skin color areas were segmented to obtain the candidate face areas. Next, the inertia weight control factors and random search factor were introduced to optimize the global search ability of particle swarm optimization (PSO). The improved PSO was adopted to optimize the initial connection weights and output thresholds of the neural network. After that, a strong AdaBoost classifier was designed based on optimized weak BPNN classifiers, and the weight distribution strategy of AdaBoost was further improved. Finally, the improved AdaBoost was employed to detect the final face areas among the candidate areas. Simulation results show that our face detection method achieved high detection rate at a fast speed, and lowered false detection rate and missed detection rate.

An ICSC Model for Detecting Human Skin in JPEG Images

The detection of human skin color has proven to be a useful and robust technique for detecting nude images, face detection, localization and tracking. This paper presents an Improved Chromatic Skin Color model to detect the human skin in JPEG images; the ICSC model detected the human skin with detection rates more than 90%. A threshold method and 2D Gaussian model will improve the accuracy of skin regions detected

Hand Gesture Recognition Using PCA, KNN and SVM

To interact with world using expressions or body movements is comparatively effective than just speaking. Gesture recognition can be a better way to convey meaningful information. Communication through gestures has been widely used by humans to express their thoughts and feelings. Gestures can be performed with any body part like head, face, hands and arms but most predominantly hand is use to perform gestures, Hand Gesture Recognition have been widely accepted for numerous applications such as human computer interactions, robotics, sign language recognition, etc. This paper focuses on bare hand gesture recognition system by proposing a scheme using a database-driven hand gesture recognition based upon skin color model approach and thresholding approach along with an effective template matching with can be effectively used for human robotics applications and similar other applications .Initially, hand region is segmented by applying skin color model in YCbCr color space. Y represents the luminance and Cb and Cr represents chrominance. In the next stage Otsu thresholding is applied to separate foreground and background. Finally, template based matching technique is developed using Principal Component Analysis (PCA), k-nearest neighbour (KNN) and Support Vector Machine (SVM) for recognition. KNN is used for statistical estimation and pattern recognition. SVM can be used for classification or regression problems.

ANALISIS IDENTIFIKASI WAJAH MENGGUNAKAN GABOR FILTER DAN SKIN MODEL

- Identification of faces in digital images is a complex process and requires a combination of various methods. The complexity of facial identification is increasing along with the increasing need for high accuracy of facial images. This research analyzes the combination of Skin Color Model and Gabor Filters in the process of identifying facial identities in digital images. The Skin Color Model method is used to separate the face area from facial images based on skin color values on facial images. The face area is then extracted using Gabor Filter. This research resulted in the highest accuracy was 93.6349%. and the lowest accuracy is around 82.45%. The implementation of a combination of Skin Color Models and Gabor Filters can be an alternative method of identifying faces in digital images. Keywords - Digital Image, Face Identification, Skin Color Model, Gabor Filter.