Empirical Evaluation of Dissimilarity Measures for Color and Texture
نویسندگان
چکیده
This paper empirically compares nine image dissimilarity measures that are based on distributions of color and texture features summarizing over 1,000 CPU hours of computational experiments. Ground truth is collected via a novel random sampling scheme for color, and via an image partitioning method for texture. Quantitative performance evaluations are given for classification, image retrieval, and segmentation tasks, and for a wide variety of dissimilarity measures. It is demonstrated how the selection of a measure, based on large scale evaluation, substantially improves the quality of classification, retrieval, and unsupervised segmentation of color and texture
منابع مشابه
An Empirical Study and Comparative Analysis of Content Based Image Retrieval (CBIR) Techniques with Various Similarity Measures
Content Based Image Retrieval (CBIR) is a process in which for a given query image similar images will be retrieved based on the image content similarity. Image content refers to its visual features, which are mathematical representations of a digital image. The image retrieval task primarily depends on image feature extraction and similarity measurement between the feature vectors. The perform...
متن کاملAdaptive histograms and dissimilarity measure for texture retrieval and classification
Histogram-based dissimilarity measures are extensively used for content-based image retrieval. In an earlier paper [1], we proposed an efficient weighted correlation dissimilarity measure for adaptive-binning color histograms. Compared to existing fixed-binning histograms and dissimilarity measures, adaptive histograms together with weighted correlation produce the best overall performance in t...
متن کاملModeling of Texture and Color Froth Characteristics for Evaluation of Flotation Performance in Sarcheshmeh Copper Pilot Plant, Using Image Analysis and Neural Networks
Texture and color appearance of froth is a discreet qualitative tool for evaluating the performance of flotation process. The structure of a froth developed on the flotation cell has a significant effect on the grade and recovery of copper concentrate. In this work, image analysis and neural networks have been implemented to model and control the performance of such a system. The result reveals...
متن کاملA New Similarity Measure for Random Signatures: Perceptually Modified Hausdorff Distance
In most content-based image retrieval systems, the low level visual features such as color, texture and region play an important role. Variety of dissimilarity measures were introduced for an uniform quantization of visual features, or a histogram. However, a cluster-based representation, or a signature, has proven to be more compact and theoretically sound for the accuracy and robustness than ...
متن کاملAdaptive Matrices for Color Texture Classification
In this paper we introduce an integrative approach towards color texture classification learned by a supervised framework. Our approach is based on the Generalized Learning Vector Quantization (GLVQ), extended by an adaptive distance measure which is defined in the Fourier domain and 2D Gabor filters. We evaluate the proposed technique on a set of color texture images and compare results with t...
متن کامل