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RISS 인기검색어
- 검색키워드
- 저자 : Hiyam Hatem (검색결과 6 건)
- 무료
- 기관 내 무료
- 유료
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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.
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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.
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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.
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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.
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A Survey of Digital Image Watermarking Optimization based on Nature Inspired Algorithms NIAs
Jumana Waleed,Huang Dong Jun,Thekra Abbas,Saad Hameed,Hiyam Hatem 보안공학연구지원센터 2014 International Journal of Security and Its Applicat Vol.8 No.6
Nature-inspired algorithms (NIAs) have gained a significant popularity in recent years to tackle hard real world problems and solve complex optimization functions whose actual solution does not exist. Many new algorithms have been developed which show their capabilities almost in every aspect, where rapid solutions are needed. A survey of the NIAs that are used to find the optimal digital image watermarking has been presented in this paper. Different paradigms have been considered, Genetic algorithm (GA), particle swarm optimization (PSO), differential evolution (DE), ant colony optimization (ACO), bee algorithm (BA), cat swarm optimization (CSO), firefly algorithm (FA) and cuckoo search algorithm (CS) that help to find the optimal digital image watermarking.
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An Immune Secret QR-Code Sharing based on a Twofold Zero-Watermarking Scheme
Jumana Waleed,Huang Dong Jun,Sarah Saadoon,Saad Hameed,Hiyam Hatem 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.4
A robust twofold zero-watermarking scheme for secret QR-Code (Quick Response Code) sharing is proposed in order to increase the security of commercial activities on the internet and media. In this paper we will present a twofold scheme for zero-watermarking to be used for copyright protection, implemented in discrete wavelet transform (DWT) as the first fold and discrete cosine transform (DCT) as a second fold for color images in which the visual secret sharing is used to generate unexpanded master and secret shares for the same QR-Code watermark. The experimental results indicate that the proposed scheme is highly robust and the QR-Code can be decodable even after different types of attack being applied.
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