Technique Description Performance Evaluation Matrices

873 Words Nov 24th, 2016 4 Pages
Technique Description Performance Evaluation Matrices Reference
Markovian stochastic mixture approach It is composed of three main sections which includes face detection, face alignment and face recognition. Usually these sections are executed in bottom up approach. CSU Face Identification Evaluation System is used to evaluate the performance of the technique and it is found that bottom up approach proposed has better identification rate tested on 104 images. [9] orthogonal locality preserving projection (OLPP) method Novel face recognition method based on projections of high-dimensional face image representations into lower dimensionality and highly discriminative spaces. Tested for a number of datasets and it is found that accuracy of image recognition for proposed approach is higher. The results are evaluated for different resolutions of the image and it is found that even for low resolution accuracy is considerably more for proposed approach. [11]
Multi-algorithmic approach It is combination of Principal component analysis (PCA), Discrete cosine transform (DCT), Template matching using correlation (Corr) and partitioned iterative function system (PIFS). All the hybrid approaches have been evaluated using accuracy i.e recognition rate. It is found recognition rate is higher for combination of all four approaches. Correlation function is used to calculate recognition rate. [12]
KNN approach based on LPP First the vectors of source faces and target faces into feature…
Open Document