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In this paper, we propose an integrated approach for human detection in surveillance video. In our approach, the moving object is extracted by background subtraction, and the background model is updated by the first order recurrence filter. Then, two complementary shape features are extracted for moving object classification. They are contour-based description: Fourier descriptor and region-based...
Progress in shape based object recognition methods involving either the boundary based or region based methods and their relative popularity is presented. Prevalence of boundary in almost of types and their shapes discriminating features are discussed. Limitations to boundary based methods viz. sensitivity to noise and variations are detailed. The present paper proposes to overcome these limitations...
In this paper, we present a novel generalized Segment-Forest Model (SFM) to segment an object as well as label all the object's semantic parts simultaneously. Segment-Forest is composed by various generated segment trees that act directly on super pixels. Unlike recent works, SFM does not need the prior information like skeleton to capture the core structure of an object, but actively learns the structure...
Script identification at the word level is challenging because of complex backgrounds and low resolution of video. The presence of graphics and scene text in video makes the problem more challenging. In this paper, we employ gradient angle segmentation on words from video text lines. This paper presents new Gradient-Angular-Features (GAF) for video script identification, namely, Arabic, Chinese, English,...
To detect and identify viruses in electron microscopy images is crucial in certain clinical emergency situations. It is currently a highly manual task, requiring an expert sitting at the microscope to perform the analysis visually. Here we focus on and investigate one aspect towards automating the virus diagnostic task, namely recognizing the virus type based on their texture once possible virus objects...
We proposed a framework for human action recognition by learning pose dictionary as the human appearance representation. At first, the shape based pose feature is constructed based on the contour points of the human silhouette and invariant to translation and scaling. After the local pose features are extracted from the original videos, the class-specific dictionaries are learned individually on the...
As an increasing number of digital images are generated, a demand for an efficient and effective image retrieval mechanisms grows. In this work, we present a new skeleton-based shape retrieval algorithm, which starts by drawing circles of increasing radius around skeleton points. Since each skeleton corresponds to the center of a maximally inscribed circle, this process results in circles that are...
Effective information retrieval on handwritten document images has always been a challenging task, especially historical ones. In the paper, we propose a coarse-to-fine handwritten word spotting approach based on graph representation. The presented model comprises both the topological and morphological signatures of the handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are...
Recent works investigated the possibility to design solutions for pattern recognition problems by exploiting the huge amount of work done in bioinformatics. If the pattern recognition problem is cast in biological terms, then a huge range of algorithms, exploitable for classification, detection, visualization, etc. can be effectively borrowed. In this paper, we exploit biological sequence alignment...
This paper will focus on the issue of human body dissimilarity detection from 3D bodyscan. A new 3D human body shape descriptor is proposed as well as a global geometric shape analysis of body shape surfaces coupled with anthropometrics points. The aim of this research is then to establish a new methodology of human body morphology shapes detection in order to define the morphotypes of a given population...
Biometrics-based hand authentication is among the most popular biometrics used to automatically characterize a person especially in forensic applications. Hand recognition systems are able to confirm or deny the identity of a claimed person because they do not cause anxiety for the users. However, different individuals may have almost similar hands. Therefore, the performance of the hand verification...
In this paper, we propose an orthonormal wavelet basis having a dilation factor (R + 1)/ R with an arbitrary real number R > 0. This orthonormal wavelet basis requires an infinite number of wavelet shapes when the dilation factor (R + 1)/ R is ir-rational, and (R + 1)/ R can be taken an arbitrary real number greater than 1 with the appropriate real number R > 0.
In this research, we propose a system of vowel recognition on the shape of the lips using a neural network backpropagation. For recognizing the shape of the vowels in the lips by image capturing through the webcam, and then processed through image processing which includes edge detection, filtering, mouth feature extraction, integral projection and vowels recognition on the lips using a back propagation...
Shape, color and texture are the most important discriminative elements for content based image retrieval. Fourier descriptors are widely used in shape based image retrieval problems. This paper presents a novel method of extracting Fourier descriptors from the simplest shape signature - complex coordinates. Instead of the commonly used scale normalization with the magnitude of the first harmonic,...
In this paper, we propose a framework to discover and segment favorite object from the natural images. The main idea is to first generate the shape based common template of the favorite object using the images collected from the web. Then, the common template is used to extract the favorite object from the original images. In the common template generation, co-segmentation is used to provide the initial...
In this paper, we propose a new image labeling algorithm for object analysis of the binary images. With one-scan process, the foreground (object) pixel is assigned a provisional label, and label equivalences between provisional labels are merged later. Our approach merges the region of the labeling of the foreground image during the one-scan labeling process. Compared with the existing conventional...
With the development of internet technologies and communication services, message transmissions over the internet still have to face all kinds of security problems. Hence, how to protect secret messages during transmission becomes a challenging issue for most of the researchers. It is worth mentioning that many applications in computer science and other related fields rely on steganography and watermarking...
Based on analysis of plate shape defect pattern in cold rolling, a defect recognition method using RBF-BP combinational neural network model optimized by genetic algorithm is proposed in this paper. The method makes use of genetic algorithm to optimize the weights and thresholds of the input layer, hidden layer and output layer in the RBF-BP network, and a GA-RBF-BP network model is formed. It can...
Smartphones are rapidly increasing in this technological world, in that visual media is the most important thing in mobile arena and due to visual graphical world everyone wants high graphical visual media. Now a day demands of videos and images are very high, some devices support HD images and HD videos and some does not. It is due to the low resolution support of the device like some small screened...
The most widely used in the field of visual object recognition descriptive features are shape based features. Identify objects in the image, contour and region shape descriptors based on two main topics to be examined. In order to describe objects with lesser number of descriptors, linear or cubic curves are fitted to the contours of the objects. The end points of these finite length curves are usually...
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