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Image segmentation is one of the most significant tasks in computer vision. Since automatic techniques are hard for this purpose, a number of interactive techniques are used for image segmentation. The result of these techniques largely depends on user feedback. It is difficult to get good interactions for large databases. On the other hand, automatic image segmentation is becoming a significant objective...
In this paper, a new technique, i.e. decremental depth bunches have been presented where two facial discriminating mechanisms have also been implemented for recognizing the individuals. Notably, based on variations of the depth values, different bunches of face regions (i.e. the small components) are extracted by differentiating the depth information that eventually describes detailed facial surface...
Infantile hemangiomas (IH) are benign vascular tumors, most of them appearing in the first weeks and developing until six months of age. The evaluation of the lesion size is usually made by the physician through manual measurement, which is inaccurate. This paper presents an algorithm for the automatic segmentation of the hemangioma region, relying on the Maximum a Posteriori (MAP) classification...
This paper presents an iris recognition system with a self-developed elliptic curve algorithm or hash. The system was written in Python with the OpenCV library. This iris recognition system is faster than standard systems because the extraction of the iris was done on a grayscale image. To test the elliptic curve hash, iris recognition system, and computation time, images from the UBIRIS database...
In this work, the merits of class-dependent image feature selection for real-world material classification is investigated. Current state-of-the-art approaches to material classification attempt to discriminate materials based on their surface properties by using a rich set of heterogeneous local features. The primary foundation of these approaches is the hypothesis that materials can be optimally...
The problem of sparse wideband spectrum sensing (WBSS) of multiple primary users (PUs) is considered in this paper. Assuming all PUs have a similar brick-type spectrum, we can employ sub-Nyquist sampling for the wideband signal, while still being able to identify the activities of all PUs. First, we estimate the Welch power spectral density (PSD) of the aliased signal, and then apply the multi-scale...
Research about vehicle recognition and adaptive cruise control is emerging recently, using various sensory resources. There are many sensors like cameras, GPS, accelerometers, radars etc., which are used for detecting edges of the road, traffic signs, cars or pedestrians. There are many different sensors to access the objects' data information. This paper presents defining the width of the road and...
Manual identifying region with visual attention in image/video frames is not a facile task. An algorithm which automatically reveals salient region from a single image is presented. The challenging problem of saliency detection is tackled by the Delaunay triangulation with an advanced salient criteria. The criteria addresses to difference of intensive value and image feature which is based on local...
This paper presents a method for face recognition using local directional number pattern (LDN). LDN adopts encoding the directional pattern of the face and produces a more selective code than methods listed in the literature. The directional patterns are computed using the compass mask and the information is encoded using the prominent direction indices (directional numbers) and sign — which distinguishes...
A novel method for the detection and segmentation of nuclei and cells in Pap smear images is introduced. The method is based on a geometric analysis of iso- and edge-contours. For nuclei detection we employ isocontours taken at different levels of intensity and we report best detection (object) recall values as well as best segmentation precision values. For cell outline detection, we employ traditional...
The study of algorithms for iris recognition is an area of continued growth. Although a variety of methods have been proposed, this paper focuses on the analysis and implementation of an algorithm which consists of the basic steps for iris recognition- including preprocessing, segmentation, and normalization, as well as features extraction and matching- on a low-cost, low-power ARM based board, BeagleBone...
Breast occupies over Pectoral muscle (PM) which is a predominant portion in Medio-Lateral Oblique (MLO) view of mammogram. The similarity in density among PM area and the breast region may generate false positive results which can adversely affect early breast cancer detection. Noise, wedges, opaque markers etc along with labels are unnecessary in mammographic images. The suspicious segments of PM...
Nowadays, electronic toll collection (ETC) is used extensively in many countries and places, but many drivers evade detection by covering, altering or otherwise obscuring their license plates. In order to detect vehicles attempting to evade paying tolls, this study aims to identify vehicles without requiring the license plate information. Unlike traditional vehicle license plate recognition, in this...
Galaxies in the universe are commonly classified by their morphology, or visual appearance. The morphology of a galaxy tells us about the history and physical make-up of the galaxy. With the fast pace at which digital galaxy images are captured and a slow and biased human pattern recognition process, finding an efficient way to automate the galaxy image classification process can help advance the...
This study applies a novel approach to identify the research fronts of literature in tourism over the past decades. A research front is a coherent topic addressed by a group of researchers in recent years. It is difficult to adopt any traditional methodology to explore the research fronts of tourism literature due to the large amount of data. We retrieve tourism articles over the period 1977 to 2013...
Graph Matching (GM) plays an essential role in computer vision and machine learning. The ability of using pairwise agreement in GM makes it a powerful approach in feature matching. In this paper, a new formulation is proposed which is more robust when it faces with outlier points. We add weights to the one-to-one constraints, and modify them in the process of optimization in order to diminish the...
In Image Forensics, very often, copy-move attack is countered by resorting at instruments based on matching local features descriptors, usually SIFT. On the other side, to overcome such techniques, smart hackers can try firstly to remove keypoints before performing image patch cloning in order to inhibit the successive matching operation. However, keypoint removal determines per se some suspicious...
2D-to-3D conversion is an important task for reducing the current gap between the number of 3D displays and the available 3D content. Here, we present an automatic 2D-to-3D image conversion approach based on machine learning principles. Stemming from the hypothesis that images with a similar structure have likely a similar 3D structure, the depth of a query color image is estimated using a color plus...
A novel approach to land masking in synthetic aperture radar (SAR) images is designed and implemented. The developed algorithm takes as input an archived shoreline from a public domain database and modifies it to draw the actual shoreline on SAR images by analysing backscatter values. Starting with data from the GSHHS (the global self-consistent hierarchical high-resolution shoreline database), coastline...
The use of sweat pores in fingerprint recognition is becoming increasingly popular, mostly because of the wide availability of pores, which provides complementary information for matching distorted or incomplete images. In this work we present a fully automatic pore-based fingerprint recognition framework that combines both pores and ridges to measure the similarity of two images. To obtain the ridge...
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