Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : LDA

Visual Depression Diagnosis From Face Based on Various Classification Algorithms

Sana A. Nasser; Ivan A. Hashim; Wisam H. Ali

Engineering and Technology Journal, 2020, Volume 38, Issue 11, Pages 1717-1729
DOI: 10.30684/etj.v38i11A.1714

Most psychologists believe that facial behavior through depression differs from facial behavior in the absence of depression, so facial behavior can be utilized as a dependable indicator for spotting depression. Visual depression diagnosis system (VDD) establishes dependents on expressions of the face that are expense-effective and movable. At this work, the VDD system is designed according to the Facial Action Coding System (FACS) to extract features of the face. The key concept of the Facial Action Coding System (FACS) to explain the whole face behavior utilizing Action Units (AUs), every AU is linked to the motion of unique or maybe further face muscles. Six AUs have utilized as depression features; those action units are AUs 4, 5, 6, 7, 10, and 12. The datasets that employed to evaluate the performance of the proposed system are gathered for 125 participants (30 males, 95 females); many of them are among 17-60 years of age. At the final step of the current system, four kinds of classification techniques were applied separately; those classifiers algorithms are KNN, SVM, PCA, and LDA. The outcomes of the simulation indicate that the best outcomes are achieved utilizing the KNN and LDA classifiers, where the success rate is 85%. New classification methods in the VDD system are the key contributions of this research, gather real databases that can utilize to compute the performance of every other VDD system based on face emotions, and choose appropriate features of the face.

Real Time Face Recognition in Video Using Linear Discriminate Analysis and Local Binary Patterns

Yossra Hussain Ali; Istabraq Saleem Abed Aljabar

Engineering and Technology Journal, 2015, Volume 33, Issue 4, Pages 690-701

The need for robust recognition system in applications of surveillance and biometrics is increasing with the advancements in technology. The conventional method of passwords and pin numbers can be easily hacked,a so these are being rapidly replaced by more secure and reliable biometric methods. This paper produces a new real-time surveillance system in video which makes use of face characteristics of the user for correct identification. The face is first detected using Viola-Jones algorithm, then a hybrid algorithms were used to extract the features and determine the faces linear discriminate analysis and local binary patterns.The proposed approach tested and gives efficient results when compared with other previous approach.