Content Based Image Retrieval by using Multi Layer Centroid Contour Distance
نویسنده
چکیده
In this paper we present a new approach to measuring similarity between two shape of object. In conventional method, centroid contour distance (CCD) is formed by measuring distance between centroid (center) and boundary of object, but this method cannot capture if an object have multiple boundary in the same angle. We develop a novel approach feature shape by measuring distance between centroid (center) and boundary of object that can capture multiple boundaries in the same angle or multi-layer centroid contour distance (MLCCD). The experiment result on simulation dataset and plankton dataset show that the proposed method (MLCCD) better than the conventional method (CCD). Keywords— Content based Image Retrieval; CCD; MLCCD
منابع مشابه
Affine Invariant Compact Centroid Distance Shape Descriptor for Image Retrieval
Simple and fast feature extraction methods are in need today for Content Based Image Retrieval (CBIR) and object recognition applications. The work presented in this paper is contour based one dimensional shape feature extraction technique for closed contour objects. The continuous contour is normalized into ‘N’ representative points. The sector area based object area normalization (OAN) techni...
متن کاملComparison Contour Extraction Based on Layered Structure and Fourier Descriptor on Image Retrieval
In this paper, a new content-based image retrieval technique using shape feature is proposed. A shape features extracted by layered structure representation has been implemented. The approach is extract feature shape by measuring the distance between centroid (center) and boundaries of the object that can capture multiple boundaries in the same angle, an object shape that has some points with t...
متن کاملContent-Based Image Retrieval Using Salient boundary and Centroid-radii Model
In view of the instability and low efficiency of the present image retrieval method, especially for simple image comparison with some salient shapes, a new image retrieval algorithm based on salient closed boundary is presented. Firstly, the Canny operator is performed to detect edges. Secondly, the ratio contour is used to extract the most salient closed boundary of some shape from the image. ...
متن کاملA Novel Method for Content Base Image Retrieval Using Combination of Local and Global Features
Content-based image retrieval (CBIR) has been an active research topic in the last decade. In this paper we proposed an image retrieval method using global and local features. Firstly, for local features extraction, SURF algorithm produces a set of interest points for each image and a set of 64-dimensional descriptors for each interest points and then to use Bag of Visual Words model, a cluster...
متن کاملWavelet-Based Multi-level Object Retrieval In Contour Images
In this paper we present a novel approach to shape similarity estimation. The target application is content-based indexing and retrieval over large image databases. The technique is based on wavelet decomposition and uses polygon approximation over several scales. This technique uses simple features (aspect ratio, angles, distances from the centroid, distance ratios and relative positions) extr...
متن کامل