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Feature refers to some relevant information which is present on images or faces. Feature extraction used to extract those features from the face. Among that bulk of keypoints, only robust features are detected by using feature descriptors. This paper analyzes 2 robust feature detector and descriptors are: Scale-Invariant Feature Transform (SIFT) and Speeded Up Robust Features (SURF). These two robust...
Splicing, cutting and insertion are the most common operations imposed on audio files when the adversary intends to modify or fabricate the content. The detection of such kinds of tampering is still challenging in real-world applications. In this paper, a generic approach for the detection of audio tampering is proposed via the analysis of electric network frequency (ENF). Based on the fact that tampering...
It is well-known that for speaker recognition task, gender-dependent acoustic modeling performs better than gender-independent modeling. The practice is to use the gender ground-truth and to train gender-dependent models. However, such information is not necessarily available, especially if speakers are remotely enrolled. A way to overcome this is to use a gender classification system, which introduces...
In this paper, we address the task of instance-level semantic boundary detection. To this end, we generate a large database consisting of more than 10k images (which is 20 bigger than existing edge detection databases) along with ground truth boundaries between 459 semantic classes including instances from both foreground objects and different types of background, and call it the PASCAL Boundaries...
Source code reuse is a common practice in software development. Since industrial developers may accidentally reuse source files developed by open source software, clone detection tools are used to detect open source files in their closed source project. To execute a clone detection, developers need a database of existing open source software. While a web-service providing clone detection using a centralized...
Nowadays, many pedestrians are victims of road accidents. Several artificial vision solutions, based on pedestrian detection, have therefore been developed to assist drivers and reduce the accident rate. But most of the proposed pedestrian databases make it possible to test detection only in favorable conditions. The main goal of this research is to provide a learning and testing environment for the...
Goal: Mammography is the most effective technique for breast cancer screening, and the detection of abnormalities plays a vital role in Computer Aided Detection (CAD) system. This paper proposes a detection method for abnormal mammograms based on improved saliency detection. Methods: The proposed method comprises three main steps: firstly, enhance abnormal mammograms using dual morphological top-hat...
Malware is an international software disease. Research shows that the effect of malware is becoming chronic. To protect against malware detectors are fundamental to the industry. The effectiveness of such detectors depends on the technology used. Therefore, it is paramount that the advantages and disadvantages of each type of technology are scrutinized analytically. This study's aim is to scrutinize...
our task of video copy detection system aims to locate vicdeo segments that are partially copied or near-duplicated versions from an archive of reference videos. In 2010, video copy detection problem was sometimes considered as a solved problem, since previous research within this area used either small-scale or large-scale datasets (e.g. TRECVID 2009, Muscle-VCD) with pre-defined simulated videos...
Ischemic Heart Disease (IHD) and stroke are statistically the leading causes of death world-wide. Both diseases deal with various types of cardiac arrhythmias, e.g. premature ventricular contractions (PVCs), ventricular and supra-ventricular tachycardia, atrial fibrillation. For monitoring and detecting such an irregular heart rhythm accurately, we are now developing a very cost-effective ECG monitor,...
Head pose estimation is not only a crucial preprocessing task in applications such as facial expression and face recognition, but also the core task for many others, e.g. gaze; driver focus of attention; head gesture recognitions. In real scenarios, the fine location and scale of a processed face patch should be consistently and automatically obtained. To this end, we propose a depth-based face spotting...
Algorithms for facial landmark detection in real-world images require manually annotated training databases. However, the task of selecting or creating the images and annotating the data is extremely time-consuming, leaving researchers with the options of investing significant amounts of time for creating annotated images optimized for the given task or resigning from creating such hand-labeled databases...
Automatic Vehicle Location (AVL) is becoming an important tool in Intelligent Transportation Systems (ITS) in the past few years, as it is an effective way of collecting and transmitting data regarding the vehicle's trip for real-time or future use. A methodology for analyzing the state of the art regarding the application of these systems is proposed in a form of a systematic literature review, by...
Initialization and feature selection are crucial in supervised landmark detection. Mismatching caused by detector error and discrepant initialization is very common in these existing methods. To solve this problem, we proposed a new method, which includes a new initialize model and multitask feature learning, for the robust facial landmark localization. In our new method, firstly, a fast detection...
In this paper we propose a method for automatic collimation border rotation angle detection. Algorithm utilizes pooling of image gradients based on their orientations to form a histogram of oriented gradients (HOG) with the goal of determining the dominant gradient orientation in the image as collimation border rotation angle. To avoid accumulation of lower magnitude gradients only a percentage of...
As radiographic imaging is one of the most used medical imaging modalities, it has been a subject of various research in the domains of image processing and computer vision. Expert annotated databases are needed to enable easier algorithm development, validation and verification. From algorithm development standpoint, image information such as the existence and position of collimation, existence of...
Retinal vessel segmentation plays a key role in the detection of numerous eye diseases, and its reliable computerised implementation becomes important for automatic retinal disease screening systems. A large number of retinal vessel segmentation algorithms have been reported, primarily based on three main steps including making the background uniform, second-order Gaussian detector application and...
Customs continue to use a wide range of technology in protecting against terrorism and the movement of illicit trade and prohibited imports. The throughput of scanned vehicles and cargo increases and just keeps on growing. Therefore, the need of automated algorithms to help screening officers in inspection, examination or surveillance of vehicles and containers is crucial. In this context, the successful...
SIMPLE (Searching Images with MPEG-7 (& MPEG-7-like) Powered Localized dEscriptors) is a model that proposes the reuse of well-established global descriptors by localizing their description mechanism on image patches located by local features' detectors. Having displayed impressive retrieval results on two different databases, in this paper we extend the family by replacing the originally picked...
Correct nuclide identification is critical for first responders. It is the final result of the complex chain occurring in a detector: a spectrum with poor statistics in a variable environment is recorded then analyzed. Industries are facing a complex challenge, as they have to design instruments that can identify materials that for the most part are difficult to obtain. Modelling a source is a viable...
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