Head Pose Estimation Based On Detecting Facial Features

Hiyam Hatem,Zou Beiji,Raed Majeed,Jumana Waleed,Mohammed Lutf 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.3

Head pose estimation is recently a more popular area of research. Challenging conditions, such as extreme pose, lighting, and occlusion, has historically hampered traditional, model-based methods. This paper presents a proposal of an integrated method for head pose estimation based on face detection and tracking. This method first locates certain facial features and based on their relative locations determine the head pose, the head pose estimated using coordinates of both eyes and a mouth relative to the nose as the origin of the coordinate system. The nose position is set up as the origin. The coordinates of the other parts defined from the origin, the distance between the face parts normalized so that the coordinates are independent of the image size. For facial feature detection from the detected face region, Haar-like feature utilized along with AdaBoost learning, the Adaboost learning algorithm used for creating optimized learning data. From the experiments, the proposed approach shows robustness in face and facial feature detection and eventually produces better results in estimating head pose rather than simply using Haar-like feature for both face and facial feature detection. The computational cost is low because it uses only those three points.

Face Detection and Pose Estimation Based on Evaluating Facial Feature Selection

Hiyam Hatem,Zou Beiji,Raed Majeed,Mohammed Lutf,Jumana Waleed 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.2

The detection of faces is one of the most requesting fields of research in image processing and Visual estimation of head pose is desirable for computer vision applications such as face recognition, human computer interaction, and affective computing. In this paper, we propose completed method for face pose estimation, face and face parts detection, feature extraction, tracking. This paper proposes using an improved AdaBoost algorithm, which is much better than normal AdaBoost. We use the de-facto Viola- Jones method for face and face part detection. From the robustness property of Haar-like feature, we first construct the strong classifier more effective to detect rotated face, and then we propose a novel method that can reduce the training time. We adopt affine motion model estimation as a tracking method. The combination enables efficient detection around the search area limited by tracking. Experimental results demonstrated its effectiveness and robustness against different types of detection and pose estimation in the input face images, including faces that appear in a wide range of image positions and scales, and also complex backgrounds, occlusions, illumination variations and multi-pose head images.

Ancient Cuneiform Text Extraction Based on Automatic Wavelet Selection

Raed Majeed,Zou Beiji,Hiyam Hatem,Jumana Waleed 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.6

Ancient Iraq was the home of a major urban civilization which developed during 4000-3000 BCE. The Sumerians, who lived in Mesopotamia in southern Iraq, invented the cuneiform system of writing, which was an essential element of Sumerians culture. The translation of cuneiform is a highly complicated process. It is only in comparatively recent years that the grammar has been scientifically established, while the lexical problems are still numerous and far from resolved. Furthermore, most of the Sumerians tablets lost only few old images left, some of it saved in a special collection or worldwide museums. In this paper, we present a novel method used to obtain the cuneiform text from old Sumerian clay tablets, proposed method based on automatically select wavelet bases which it is essential and critical issues for wavelet algorithm implementation. Our procedure offers the archaeological and Cuneiformest an easy, fast and active method for extracting the cuneiform sentences. Experimental results of sample images show that the proposed system has superior result.

A Novel Algorithm for Fire/Smoke Detection based on Computer- Vision

Jean Paul Dukuzumuremyi,Beiji Zou,Damien Hanyurwimfura 보안공학연구지원센터 2014 International Journal of Hybrid Information Techno Vol.7 No.3

Nose Tip Detection in 3D Face Image Based On Maximum Intensity Algorithm

Raed Majeed,Hiyam Hatem,Zou Beiji 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.5

In order to increase the ability to track face movements with large head rotations, a 3D shape model is used in the system. In this paper, we present a robust nose tip detection method in 3D facial image that handling facial expression and hair occlusion. The 3D face smoothed by weighted median filter, the holes are filled by linear interpolation during the re-sampling phase and the 3D Gaussian filter is used to remove noise. Since the database, mesh contains unimportant parts like neck, shoulder, clothes and hair that can also change the overall appearance of a face. We propose a 3D mask to cut the face and crop useful part, which helps us to achieve sufficient accuracy for noise detection. Nose localization is one of the most significant tasks of any facial classification system, compared to other facial landmarks. We proceed to detect the point N from the front image following the assumption that the relevant point has the highest value of the Z axis. In this framework, the face model is determined from a frontal 3D face image. In this experiment, the performance rate is improved from 90.1% to 98.3%. As indicated by the experimental result, the proposed binary mask with maximum intensity method provides a significant improvement in performance of nose tip detection, also it success in different facial expression.

Printed Document Authentication Using Two-Dimensional (2D) Barcodes and Image Processing Techniques

Mohammed AL-Gawda,Zou Beiji,Nurudeen Mohammed 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.8

Advancements in information and communication technologies have made it easier to forge printed documents these days. Forgery of printed document could have serious repercussions including financial losses, so maintaining the reliability of valuable documents is one that is timely and necessary. The document authentication approach in this study is one that involves tracing of the origin of a document through its contents. The approach explores viability of embedding certain information on printed documents for authentication purposes. Such information could be extracted from the content of documents, which can be divided into two: the context, which includes the text, figures and shapes and the visual attributes of the document, such as its color and design. In short, this study presents a practical and secure method to prevent the forgery of important documents. The proposed method makes use of the public key infrastructure (PKI) and Quick Response (QR) code and the cryptographic hash algorithm shows robustness to printing or scanning noise. The method also makes use of the unique tracking numbers such as device serial numbers, and timestamps enhance the security. To test the feasibility of the method several experiments were perform and the experimental results showed significant improvement in printed document authentication.

Visibility detection approach to road scene foggy images

( Fan Guo ),( Hui Peng ),( Jin Tang ),( Beiji Zou ),( Chenggong Tang ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.9

A cause of vehicle accidents is the reduced visibility due to bad weather conditions such as fog. Therefore, an onboard vision system should take visibility detection into account. In this paper, we propose a simple and effective approach for measuring the visibility distance using a single camera placed onboard a moving vehicle. The proposed algorithm is controlled by a few parameters and mainly includes camera parameter estimation, region of interest (ROI) estimation and visibility computation. Thanks to the ROI extraction, the position of the inflection point may be measured in practice. Thus, combined with the estimated camera parameters, the visibility distance of the input foggy image can be computed with a single camera and just the presence of road and sky in the scene. To assess the accuracy of the proposed approach, a reference target based visibility detection method is also introduced. The comparative study and quantitative evaluation show that the proposed method can obtain good visibility detection results with relatively fast speed.

A Secure Medical Information Management System for Wireless Body Area Networks

( Xiyao Liu ),( Yuesheng Zhu ),( Yu Ge ),( Dajun Wu ),( Beiji Zou ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.1

The wireless body area networks (WBANs) consist of wearable computing devices and can support various healthcare-related applications. There exist two crucial issues when WBANs are utilized for healthcare applications. One is the protection of the sensitive biometric data transmitted over the insecure wireless channels. The other is the design of effective medical management mechanisms. In this paper, a secure medical information management system is proposed and implemented on a TinyOS-based WBAN test bed to simultaneously address these two issues. In this system, the electronic medical record (EMR) is bound to the biometric data with a novel fragile zero-watermarking scheme based on the modified visual secret sharing (MVSS). In this manner, the EMR can be utilized not only for medical management but also for data integrity checking. Additionally, both the biometric data and the EMR are encrypted, and the EMR is further protected by the MVSS. Our analysis and experimental results demonstrate that the proposed system not only protects the confidentialities of both the biometric data and the EMR but also offers reliable patient information authentication, explicit healthcare operation verification and undeniable doctor liability identification for WBANs.