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This paper proposes a novel and efficient shape-based approach for hand dorsal vein recognition. A coarse-to-fine segmentation method is first introduced to precisely detect the boundaries of the vein areas. A generalized graph model, namely Width Skeleton Model (WSM), is built then, which takes both the topology of the vein network and the width of the vessel into account, thereby achieving more...
Efficiency and effectiveness are two key factors to evaluate a human segmentation algorithm for real vision applications. However, most existing algorithms only focus on one of them. That is, fast and accurate human segmentation is not yet well addressed. In this paper, we propose a super-fast and highly accurate human segmentation method with very deep convolutional neural networks. We also provide...
In this paper a bottom-up approach for detecting and recognizing objects in complex scenes is presented. In contrast to top-down methods, no prior knowledge about the objects is required beforehand. Instead, two different views on the data are computed: First, a GIST descriptor is used for clustering scenes with a similar global appearance which produces a set of Proto-Scenes. Second, a visual attention...
The automated computation of muscle volume from MRI of human legs is an open problem in the biomédical imaging community. Such automation has the potential to provide an objective measure of effectiveness of pre- and post-surgery treatments. In this paper, we take a step toward automation by proposing a framework for user interactive segmentation of MRI of human leg muscles. Our framework is built...
Fingerprint segmentation is one of the most important preprocessing steps in an automatic fingerprint identification system (AFIS). It is used to separate a fingerprint area (foreground) from the image background. Accurate segmentation of a fingerprint will greatly reduce the computation time of the following processing steps, and discard many spurious minutiae. In this paper, a new segmentation algorithm...
What makes a target object stand out and get attended to immediately? Previous work suggests that a salient object carries discriminating features, which make it distinct from its neighborhood. Many models have approached this problem using different methods of distinctness computation. A class of models exploit global feature statistics and adapt a region-based approach to identify distinct patterns,...
Automatic organ segmentation on a full-body scan image is a challenging task as most of the organ segmentation methods require a prior knowledge about the position of the given organ within the image. In this paper we show, how discriminately trained deformable part model can be used to acquire this prior knowledge by constructing a multi-organ detection system based on it.
Vessel segmentation is a challenging task due to the complexity of vascular networks and limitations of imaging modalities to accurately capture thin structures. Analytical models based on geometric appearance and/or edge-based assumptions have been shown to be sub-optimal in segmenting vessels. In this paper, a novel approach for learning vessel appearance models from localized-vessel image patches...
In this paper, computed tomographic (CT) images were investigated to develop a computer-aided system to discriminate different lung abnormalities. These were done by analyzing Data recorded for healthy subjects and patients suffering from lung asthma and emphysema diseases were considered. The techniques for utilized feature extraction included statistical, intensity, and morphological features as...
Image-based building reconstruction is a hot point in computer vision and computer graphics, but few works have done on reconstruction from a single image because it is an ill-conditional problem and is very difficult to resolve. In this paper, we present an efficient method by matching contours between image and projection of 3D models. Our method simplifies the reconstruction process and avoids...
We present an algorithm for 3d pose estimation of articulated people in natural images. The poses are disassembled into a collection of local patches and a new pose is inferred by assembling the local patches. This concept allows inference of a wide variety of poses from a small number of training patches. The actual process is realized efficiently by a novel voting scheme where each local patch extracted...
Questioned document examination is extensively used by forensic specialists for criminal identification. This paper presents a writer recognition system based on allographic features operating in identification mode (one-to-many). It works at the level of isolated characters, considering that each writer uses a reduced number of shapes for each one. Individual characters of a writer are manually segmented...
In this paper, we solve the searching problem by high level features used by sign language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left sign and right sign in specific areas. By computing the signs' length, position, velocity, acceleration, Fourier figure descriptor and etc, we generate the signs' dynamic features. Consequently, we segment...
Fingerprint segmentation is one of the first and most integral pre-processing steps for any fingerprint verification system, and it determines the results of fingerprint analysis and recognition. In this paper, we have proposed a novel algorithm for fingerprint segmentation. The fingerprint image gradient are discussed and its application to fingerprint segmentation is presented. Firstly, Gauss filter...
This paper introduces a novel shape model, Sparse Representation Shape Model (SRSM). Rather than for modeling specific deformable shapes, this model is specially designed for shape segmentation and matching. This model is utilized under the framework of Active Shape Models (ASM). Unlike the Linear Point Distribution Model utilized by original ASM, which relies on obscure statistical boundary to do...
In this paper, we solve the searching problem by high level features used by hand language recognition. Firstly, we find the face in video frames that has complex background, and then we find the left hand and right hand in specific areas. By computing the hands' length, position, velocity, acceleration, Fourier figure descriptor and etc, we generate the hands' dynamic features. Consequently, we segment...
Lip contour extraction is crucial to the success of a lipreading system. This paper presents a lip contour extraction algorithm using localized active contour model with the automatic selection of proper parameters. The proposed approach utilizes a minimum-bounding ellipse as the initial evolving curve to split the local neighborhoods into the local interior region and the local exterior region, respectively,...
The research context of this work is dynamic texture analysis and characterization. Many dynamic textures can be modeled as a large scale propagating wave and local oscillating phenomena. The Morphological Component Analysis algorithm is used to retrieve these components using a well chosen dictionary. We define a new strategy for adaptive thresholding in the Morphological Component Analysis framework,...
We present in this paper a new approach for Arabic font recognition. Our proposal is to use a fixed-length sliding window for the feature extraction and to model feature distributions with Gaussian Mixture Models (GMMs). This approach presents a double advantage. First, we do not need to perform a priori segmentation into characters, which is a difficult task for arabic text. Second, we use versatile...
We investigate the probability tree models to approximate skin and non-skin distributions. These models have presented good results in solving the skin detection problem. However, there are two main disadvantages of the existing skin/non-skin tree distributions based models: (1) the structure of some tree distributions is predefined; and (2) the inter and the intra classes of skin/non-skin are not...
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