This paper describes an efficient approach for face recognition as a two step process: 1) segmenting the face region from an image by using an appearance based model, 2) using eigenfaces for person identification for segmented face region. The efficiency lies not only in generation of appearance models which uses the explicit approach for shape and texture but also the combined use of the afore...

Image matching using feature extraction is an important issue in computer vision tasks. The main drawback of matching process is the bottleneck problem that rapidly appeared when the number of features increased. This paper produced an adaptive approach to improve Scale Invariant Feature Transform (SIFT) matching. The main idea is to increase the number of SIFT points by using Adaptive PCA in w...

In this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and enhance most important ones - healthy cells (erythrocytes) pathologic (echinocytes). separated analyzed terms of their features by eigenfaces method. basis designing neural network classifier, learned ...

In the present paper a face recognition technique is developed based on depth and colour information. The main objective of the paper is to evaluate three different approaches (colour, depth, combination of colour and depth) for face recognition and quantify the contribution of depth. The proposed face recognition technique is based on the implementation of the principal component analysis algo...

In this paper we present a simple novel approach to tackle the challenges of scaling and rotation of face images in face recognition. The proposed approach registers the training and testing visual face images by log-polar transformation, which is capable to handle complicacies introduced by scaling and rotation. Log-polar images are projected into eigenspace and finally classified using an imp...

Face recognition is gaining popularity as one of the biometrics methods for an attendance system in organization. Due to pandemic, common face needs be modified meet current needs, whereby facemask detection necessary. The main objective this paper investigate and develop a real-time based on scenarios. proposed framework consists detection, mask recognition, report generation modules. performe...

This paper presents an appearance-based holistic method for expression recognition. A two stage supervised learning approach is used. At the first stage, training images are used to compute one subspace per expression. At the second stage, the same images are used to train a classifier. In this step, Euclidean distances from each image to each particular subspace are used as the input to the cl...

Abstrak – In this paper, we propose a feature fusion method based on Canonical Correlation Analysis (CCA) for combining two feature extractors to increase robustness of face recognition against pose and illumination changes. At first holistic features, eigenfaces (PCA) and Gabor phase congruency image (GPCI) features are extracted from facial images respectively and then CCA finds the transform...

.......................................................................................................................23 Chapter 1 Introduction...............................................................................................25 1.1. Background and Motivations............................................................................25 1.2. Summary of Principle Contributions ........

As peoples use body language or non-verbal language such as gesture and facial expression in communication; computers will also be able to communicate humans .In the digital era, there are various computational models are already exist for recognition of different facial expressions (Happy, Sad, Disgust, Angry and neutral) but we are trying to propose a computational model of facial expression ...