Adaptive-Binning Color Histogram for Image Information Retrieval
نویسندگان
چکیده
From the 90's, the image information retrieval methods have been on progress. As good examples of the methods, Conventional histogram method and merged-color histogram method were introduced. They could get good result in image retrieval. However, Conventional histogram method has disadvantages if the histogram is shifted as a result of intensity change. Merged-color histogram, also, causes more process so, it needs more time to retrieve images. In this paper, we propose an improved new method using Adaptive Color Histogram (ACH) in image retrieval. The proposed method has been tested and verified through a number of simulations using hundreds of images in a database. The simulation results have quickly yielded the highly accurate candidate images in comparison to other retrieval methods. We show that ACH's can give superior results to color histograms for image retrieval.
منابع مشابه
Adaptive Binning and Dissimilarity Measure for Image Retrieval and Classification
Color histogram is an important part of content-based image retrieval systems. It is a common understanding that histograms that adapt to images can represent their color distributions more efficiently than histograms with fixed binnings. However, among existing dissimilarity measures, only the Earth Mover’s Distance can compare histograms with different binnings. This paper presents a detailed...
متن کاملThe analysis and applications of adaptive-binning color histograms
Histograms are commonly used in content-based image retrieval systems to represent the distributions of colors in images. It is a common understanding that histograms that adapt to images can represent their color distributions more efficiently than do histograms with fixed binnings. However, existing systems almost exclusively adopt fixed-binning histograms because, among existing well-known d...
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 کاملUncertainty Based Sampling Approach for Relevence Feedback in Content Based Image Retrieval
Interest in the digital images has increased enormously over the last few years, but the process of locating a desired image in such a large and varied image collection becomes very difficult. Traditionally text in different languages is used for efficient retrieval of images; it has several drawbacks such as language constraint and subjectivity of human perception. Content-based image retrieva...
متن کاملComparison Of Traditional Method of HSV Histogram Equalisation with Adaptive HSVsegmentation and Kekre Transform for Content Based Image Retrieval
Content-based image retrieval system based on an efficient combination of both colors and features is explained in this paper. According to Kekre’s Transform, feature vectors are formed using a combination of row mean and column mean of both query as well as database images, to measure the extent of similarity using Euclidian distance. Similarly, HSV color space quantifies the color space into ...
متن کامل