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In this work, we described a new two-stage hierarchical framework for mammogram retrieval. We tested the proposed approach on the reference library from USF-DDSM. For each query ROI (region of interest), the proposed scheme first computes its 14 texture and shape features, then the voting method based on five classifiers is used to classify the ROIs in the reference library, this phase eliminates...
This paper presents a new approach to 3D shape comparison and retrieval based on the computation of Gaussian transforms of the surface model on a set of points regularly distributed inside the model's bounding box. A study of the properties of the Gaussian term leads us to an efficient computation of the description. This method is evaluated on the Princeton Shape Benchmark database.
In this paper, the algorithm for 2D shape matching and retrieval is developed by using Fisher Barycenter Contour (FBcC). First, the shape is represented into 3D format using the signed enclosed area at each scale level of Barycenter Contour (BcC). Because of high dimension of the feature representation, the eigen Barycenter Contour (EBcC) is applied for dimensionality reduction. Then, the Fisher Barycenter...
Given a time-varying face image object, or only a sub-part of the image, the question of whether the template object image exists in a given image database is an important problem our days, which still remains in its infancy, due to the many challenges it involves. With the advantage of distributed computing, such as computation sharing and data storage sharing, the limitations of image retrieval...
The rapid development of technologies and steadily growing amounts of digital information highlight the need of developing an accessing system. Content-based image indexing and retrieval has been an important research area in computer science for the last few decades. The approaches of content-based image retrieval using low level features such as colour, shape and texture are investigated to create...
In this paper, we proposed a new 3D object retrieval method based on the visual keywords. In our method, the visual keywords are generated from the clusters of relative angle context distribution, which provides a statistical shape context that captures local shape characters and is also rotational and scale invariant. We also adopt the term frequency model commonly used for text retrieval to compare...
Spatial structure of objects is an important feature of images and making use of this feature properly is very important for the user in the retrieval system. However, only a third of the existing image retrieval systems use spatial features and those features are low precision features which are variant to rotation and shift. In this paper, a polygon-based spatial feature model is proposed to describe...
In this paper, a new and efficient descriptor for region-based shape representation and retrieval is presented. The proposed descriptor called sub-area shape matrix which is obtained based on the circular raster sampling technique and the axis of least inertia. An element of the sub-area shape matrix is obtained as the sum of pixel values on the region of the shape image enclosed by two neighboring...
Performance of traditional content-based image retrieval systems is far from userpsilas expectation due to the ldquosemantic gaprdquo between low-level visual features and the richness of human semantics. In attempt to reduce the ldquosemantic gaprdquo, this paper introduces a new effective image retrieval approach-the multi-step queries strategy-that facilitates retrieval of semantically similar...
We propose a new method for the recognition and retrieval of shapes whose contours are simple closed curves. First, we give a new shape representation by a sequence of 2D-vectors of angles, which is independent of rotation and scaling. Each 2D-vector captures the local shape information around a point in the contour. Next, we apply a dynamic programming method to match the points of two contours and...
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,...
Object shape is a powerful feature for content-based image retrieval. We propose a new shape contexts-based shape signature for shape retrieval. In terms of computing time, our method outperforms other approaches that calculate point correspondences based on shape contexts for shape retrieval. Consequently, our method is well suited for large databases. We demonstrate the retrieval performance of...
In this article we focus on the presentation of the inner structure of the database for the content-based image retrieval (CBIR) system containing house images. The part devoted to image processing is signalled to the extent necessary for further database (DB) structure explanations to the reader. In this paper standard DB project methods in the Oracle 10 g system have been used to generate a database...
This paper provides a novel content-based image retrieval algorithm based on ROI (Region Of Interest) by using SIFT (Scale Invariant Feature Transform) feature matching. SIFT descriptors, which are invariant to image scaling and transformation and rotation, and partially invariant to illumination changes and affine, present the local features of an image. Therefore, feature keypoints can be extracted...
A novel two-stage scheme of pornographic image detection is proposed in this paper. Specifically, we first apply the content-based image retrieval technique to find out whether human are present in the images. Then a detailed skin color analysis is performed to affirm the presence of pornographic content in the images. Experimental results show that the proposed algorithm performs well and fast in...
Arming at the problem that the features of the trademark still keep invariant after rotation, scaling and changing of the initial point, an algorithm of relational back in image retrieval using SPA was presented in this paper. The algorithm first extracts five features, and initialized the weight of each feature, then modifies the weight until the feedback from users is over. Finally, a comparison...
Mean shift clustering tends to generate accurate segmentations of color images, but choosing the scale parameters remains a difficult problem which has a strong impact on its performance. We present an adaptive image segmentation framework that achieves a task-dependent top-down adaption of the scale parameters. The proposed method can be used under the context of a relevance feedback-based content-based...
Content-based image retrieval (CBIR) techniques are becoming increasingly important in various fields. One of the most important steps in CBIR systems is feature extraction. However, using not appropriate features in heterogeneous image database during retrieval process does not provide a complete description of an image. Indeed, each feature is able to describe some characteristics related to the...
Shape descriptors have demonstrated encouraging potential in retrieving images based on image content. A number of shape descriptors have been reported in the literature. Nevertheless, most of the reported descriptors still face accuracy and computational challenges. Fourier descriptors are considered to be promising descriptors as they are based on sound theoretical foundation, and possess computational...
A novel method for content-based 2D vector image retrieval is proposed in this paper. To retrieve vector images, first, the proposed method extracts WFPs (weighted feature points) from vector images. In this extraction process, the method directly accesses the parameters of Bezier curves defining the shapes of vector images and computes WFPs of the images according to these parameters. Second, to...
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