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Mahalanobis, Jaccard and others are similarity measurements which are commonly used in sketch recognition. Attempts to improve similarity measurement can be made by manipulating formulae and reducing the testing data set used but less effort are attempted to propose algorithm. Hence, the purpose of this study is to propose a new algorithm for a better method in shape recognition. To do so, Mahalanobis...
This paper presents a method for triangular and rectangular shapes detection in a road sign recognition system based on a three step algorithm: color segmentation, shape detection and neural network classification. The shape detector is based on the evaluation of the Sobel edges and Hough images in a region of interest detected by the color-based stage. During the tests performed the shape detector...
This paper provides a sorting method for the identification of leguminous weed seeds by using clustering. The image processing methods are made use of threshold segmentation, smooth processing and edge detection etc, as well as the image processing algorithm is delivered. According to the stability and genetic characteristics describes in phytotaxonomy for leguminous weed seeds, the feature set includes...
In this paper, we present a new algorithm of snakes with geometric prior. A method of shape alignment using Fourier coefficients is introduced to estimate the Euclidean transformation between the evolving snake and a template of the searched object. This allows the definition of a new field of forces making the evolving snake to have a shape similar to the template one. Furthermore, this strategy...
In architectural and mechanical engineering, man-made CAD models often have some prominent contours and regular shapes. These features are important to the visual perception. Traditional mesh simplification methods are not very suitable for this kind of models because in the simplified results some important mini structures and shape regularities are always missed. In this paper, we propose a new...
In this paper, we present a one dimensional descriptor for the two dimensional object silhouettes associated with each level of barycenter contour for multiple views shape matching and retrieval. Firstly, the barycenter contour is applied onto the shape contour. Then the averaging multi-triangle area representation (AMTAR) at each level of barycenter contour is computed as the shape descriptor. Finally,...
The contour alignment problem, considered in this letter, is to compute the minimal distance in a least-squares sense, between two explicitly represented contours, specified by corresponding points, after arbitrary rotation, scaling, and translation of one of the contours. This is a constrained nonlinear optimization problem with respect to the translation, rotation, and scaling parameters; however,...
In this paper, a pose parameter estimation method is proposed, which provides an effective solution for the local optimal pose parameters problem in the shape distance measurements based on various level set based shape distance energy functions. To acquire invariance, explicit pose parameters representing translation, scaling and rotation are adopted in most recent level set based shape distance...
A novel touching cells splitting algorithm by using concave points and ellipse fitting is proposed to split circle-like or ellipse-like touching cells in this paper. The algorithm is divided into two parts. The first part is contour pre-processing, whose purpose is to find the concave points of the contour and separate the contour into different segments using the concave points. The second part is...
This paper describes a new approach by which a blind person can visualize the approximate shape of the image by hearing sound. Nowadays a lot of image shape approximation and representation algorithms are available, but these algorithms represent image contour as a sequence of straight line segments. This work proposed a digital image shape approximation method where a shape boundary is divided &...
Object detection in clutter or occlusion is a hard problem in computer vision. We propose an object detection method based on contour grouping. Two stages are included: a novel distance transform is applied to match templates to the test image so that candidates and locations of the object are obtained; verification using shape manifold is performed to preclude outliers and identify the prior. We...
This paper presents a contour-based approach to separate vertically attached traffic signs. The algorithm is based on using binary images which are generated by any color segmentation algorithm to represent objects which could be candidate traffic signs. Since all traffic signs are similar about their vertical axis, an improved cross-correlation algorithm is invoked to determine this similarity and...
Statistical properties of high-resolution overhead images representing different land use categories are analyzed using various local and global statistical image properties based on the shape of the power spectrum, image gradient distributions, edge co-occurrence, and inter-scale wavelet coefficient distributions. The analysis was performed on a database of high-resolution (1 meter) overhead images...
We address two-dimensional shape-based classification, considering shapes described by arbitrary sets of unlabeled points, or landmarks. This is relevant in practice because, in many applications, the points describing the shapes come from automatic processes, e.g., edge detection, thus without labels. Rather than attempting to compute point correspondences (a quagmire, when dealing with nontrivial...
Detecting and recognizing pedestrians in video footages are two essential and significant tasks in many automatic video understanding systems. In this paper, we propose an efficient approach to moving pedestrian detection and recognition in video. The testing process of this approach involves two main steps: moving edge detection and hypotheses generation. Moving edges are firstly extracted by comparing...
The paper presents a probabilistic Bayesian framework for object tracking using a combination of a corner-based model and coefficients of Undecimated wavelet packet transform (UWPT) inside a patch around each corner. This combination uses the UWPT coefficients patch helps to enrich the global representation of the object shape model by local descriptors. The goal is to maximize the posterior of the...
In this paper a new framework for personal identity verification using 3-D geometry of the face is introduced. Initially, 3-D facial surfaces are represented by curves extracted from facial surfaces (facial curves). Two alternative facial curves are examined in this research: iso-depth and iso-geodesic curves. Iso-depth curves are produced by intersecting a facial surface with parallel planes perpendicular...
We present novel, pose invariant 3D shape descriptors and we test the performance of these descriptors, when applied to the problems of nose identification and localisation in 3D face data. We generate an implicit radial basis function (RBF) model of the facial surface and construction of our novel features is based on sampling this RBF model over a set of concentric spheres to give a spherically-sampled...
Contour-based shape feature extraction is one of the important research contents in content-based medical image retrieval. The paper presents a method using Fourier descriptors with brightness. The method uses centroid distance function to compute shape signature from boundary pixels of a shape. Fourier transform is used for shape signature to compute Fourier coefficients, and standardized pixel brightness...
This paper introduces a new matching algorithm to estimate the similarity between two contour saliences by exploiting the relation between a contour and its skeleton. Some experimental results are presented and discussed in order to demonstrate the potentiality of the proposed technique.
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