In this paper, we describe an incipient method for image retrieval predicated on the local invariant shape feature, designated scalable shape context. The feature utilizes the Harris-Laplace corner to locat the fix points and coinside scale in the animal and flower image. Then, we utilize shape context to explain the local shape. Correspondence of feature points is achieved by a weighted bipartite graph matching algorithm and the homogeneous attribute between the query and the indexing image is presented by the match cost. The practical results show that our method is efficient than shape context and SIFT for the animal and flower image retrieval
Abstract—we introduce a new feature vector for shape-based image retrieval. This feature depends on ...
Successful retrieval of images by shape feature is likely to be achieved only if we can mirror human...
Similarity between shapes is often measured by computing the distance between two feature vectors. U...
Research in content-based image retrieval has been around for over a decade. While the research comm...
The emergence of digital library and multimedia database require an efficient and effective maintena...
The emergence of digital library and multimedia database require an efficient and effective maintena...
In modern visual information retrieval systems, visual content is directly addressed by features suc...
Summarization: We propose an approach for image similarity retrieval based on shape information. The...
This thesis is concerned with the problem of shape similarity retrieval in image databases. Curvatur...
Shape matching and object recognition plays an vital role in the computer vision. The shape matching...
We present a general strategy for shape-based image retrieval which considers similarity modulo a gi...
This thesis is concerned with the problem of shape similarity retrieval in image databases. Curvatur...
We present data representations, distance measures and organizational structures for fast and effici...
Abstract. In this article the use of statistical, low-level shape features in content-based image re...
We present a general strategy for shape-based image retrieval which considers similarity modulo a gi...
Abstract—we introduce a new feature vector for shape-based image retrieval. This feature depends on ...
Successful retrieval of images by shape feature is likely to be achieved only if we can mirror human...
Similarity between shapes is often measured by computing the distance between two feature vectors. U...
Research in content-based image retrieval has been around for over a decade. While the research comm...
The emergence of digital library and multimedia database require an efficient and effective maintena...
The emergence of digital library and multimedia database require an efficient and effective maintena...
In modern visual information retrieval systems, visual content is directly addressed by features suc...
Summarization: We propose an approach for image similarity retrieval based on shape information. The...
This thesis is concerned with the problem of shape similarity retrieval in image databases. Curvatur...
Shape matching and object recognition plays an vital role in the computer vision. The shape matching...
We present a general strategy for shape-based image retrieval which considers similarity modulo a gi...
This thesis is concerned with the problem of shape similarity retrieval in image databases. Curvatur...
We present data representations, distance measures and organizational structures for fast and effici...
Abstract. In this article the use of statistical, low-level shape features in content-based image re...
We present a general strategy for shape-based image retrieval which considers similarity modulo a gi...
Abstract—we introduce a new feature vector for shape-based image retrieval. This feature depends on ...
Successful retrieval of images by shape feature is likely to be achieved only if we can mirror human...
Similarity between shapes is often measured by computing the distance between two feature vectors. U...