Adaptive texture image retrieval in transform domain
نویسندگان
چکیده
A large number of algorithms have been proposed for texture image retrieval and analysis. While each algorithm has its own characteristics and is suitable for indexing some particular categories of images, there is a lacking of an effective strategy to integrate these algorithms to maximize the retrieval performance based on the algorithms available. Our first step in this direction is to build up a texture image retrieval system which adaptively chooses the “right” transform to query texture database. Experiments on the Brodatz texture set show that the adaptive image retrieval system significantly outperforms the commonly used single-algorithm based ones.
منابع مشابه
Rotation and scale invariant texture classification
Texture classification is very important in image analysis. Content based image retrieval, inspection of surfaces, object recognition by texture, document segmentation are few examples where texture classification plays a major role. Classification of texture images, especially those with different orientation and scale changes, is a challenging and important problem in image analysis and class...
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 کاملA Study on Texture Segmentation Towards Content-based Image Retrieval
Extended Abstract: Texture segmentation is an important but challenging task in image analysis or computer vision applications. Among various cues, texture plays a vital role towards object recognition. Recent studies reveal the two popular methods for texture analysis: filter bank methods and Gray level cooccurrence matrices (GLCM). In this work, we have proposed several texture features in th...
متن کاملImage Retrieval Based on Weighted Texture Features Using DCT Coefficients of JPEG Images
For texture images, an interesting method that reorders DCT coefficients to produce image sub-bands in a multiresolution decomposition-like form and computes the absolute mean value and standard deviation of each subband to construct a feature vector has been proposed in [4]. This method is called MRDCT for multi-resolution reordered DCT. One limitation of MRDCT is that all the DCT sub-bands we...
متن کاملSecond-Order Statistical Texture Representation of Asphalt Pavement Distress Images Based on Local Binary Pattern in Spatial and Wavelet Domain
Assessment of pavement distresses is one of the important parts of pavement management systems to adopt the most effective road maintenance strategy. In the last decade, extensive studies have been done to develop automated systems for pavement distress processing based on machine vision techniques. One of the most important structural components of computer vision is the feature extraction met...
متن کامل