Combining Structure, Color and Texture for Image Retrieval: A Performance Evaluation
نویسندگان
چکیده
In this paper, we combine structure, color and texture for efficient image retrieval. Structure is extracted by the application of perceptual grouping principles. Color analysis is performed by mapping all pixels in an image into a fixed color palette that uses linguistic tags to describe color content. Texture analysis is done using a bank of evensymmetric Gabor filters. A methodology for performance evaluation of these analyses is presented on a database of color images. The database has been partitioned into various classes and subclasses for quantifying the success of image query and classification. It is demonstrated that the synergy resulting from the combination of structure, color and texture is superior than using just color and texture.
منابع مشابه
Modeling 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 کاملImage retrieval using the combination of text-based and content-based algorithms
Image retrieval is an important research field which has received great attention in the last decades. In this paper, we present an approach for the image retrieval based on the combination of text-based and content-based features. For text-based features, keywords and for content-based features, color and texture features have been used. Query in this system contains some keywords and an input...
متن کاملContent Based Image Retrieval by Multi Features using Image Blocks
Content based image retrieval (CBIR) is an effective method of retrieving images from large image resources. CBIR is a technique in which images are indexed by extracting their low level features like, color, texture, shape, and spatial location, etc. Effective and efficient feature extraction mechanisms are required to improve existing CBIR performance. This paper presents a novel approach of ...
متن کاملCompresion Effects on Color and Texture Based Multimedia Indexing and Retrieval
This paper presents an evaluation of digital compression effects on content-based multimedia retrieval using color and texture attributes. Subjective evaluation tests that are applied on digital image and video databases using different compression and visual feature extraction techniques have been performed and reported. Simulations show that a satisfactory retrieval performance can be obtaine...
متن کاملRobust Method for E-Maximization and Hierarchical Clustering of Image Classification
We developed a new semi-supervised EM-like algorithm that is given the set of objects present in eachtraining image, but does not know which regions correspond to which objects. We have tested thealgorithm on a dataset of 860 hand-labeled color images using only color and texture features, and theresults show that our EM variant is able to break the symmetry in the initial solution. We compared...
متن کامل