Evaluation of Content Based Image Retrieval Systems Based on Color Feature
نویسندگان
چکیده
The inevitable growth in computer field brought a significant increase for storing large amount of images along with different kinds of complexity aspects. The need for efficient storage and retrieval of images has been recognized by having large image collections in the areas such as medicine, journalism, education, entertainment, advertisement, commerce, etc. The process of retrieving desired images from a large collection of images on the basis of features is referred as Content Based Image Retrieval (CBIR) Systems. This paper deals an assessment methodology for CBIR systems with the help of a set of distance metrics. This quantitative evaluation scheme consists of statistical models that provide an insight in assessing the capability of different CBIR systems. This model also serves as a reference for selecting particular CBIR system for any particular application domain. Index Terms – CBIR, Distance Metrics, Similarity Measurement
منابع مشابه
Image 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 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 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 کاملImage Retrieval Using Dynamic Weighting of Compressed High Level Features Framework with LER Matrix
In this article, a fabulous method for database retrieval is proposed. The multi-resolution modified wavelet transform for each of image is computed and the standard deviation and average are utilized as the textural features. Then, the proposed modified bit-based color histogram and edge detectors were utilized to define the high level features. A feedback-based dynamic weighting of shap...
متن کاملPerformance Evaluation of Medical Image Retrieval Systems Based on a Systematic Review of the Current Literature
Background and Aim: Image, as a kind of information vehicle which can convey a large volume of information, is important especially in medicine field. Existence of different attributes of image features and various search algorithms in medical image retrieval systems and lack of an authority to evaluate the quality of retrieval systems, make a systematic review in medical image retrieval system...
متن کاملEvaluation of Feature Extraction Techniques in Content Based Image Retrieval (CBIR) System
The term CBIR refers to the process of retrieving similar images from a large collection of image database. The image retrieval is done on the basis of similarity matching between query image and database images. Different feature extraction techniques are being used to extract features of an image. The important image features are Color, Texture, Shape, Spatial location, edges etc. The CBIR (C...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2009