Image Retrieval Using Vlad with Multiple Features
نویسندگان
چکیده
The objective of this paper is to propose a combinatorial encoding method based on VLAD to facilitate the promotion of accuracy for large scale image retrieval. Unlike using a single feature in VLAD, the proposed method applies multiple heterogeneous types of features, such as SIFT, SURF, DAISY, and HOG, to form an integrated encoding vector for an image representation. The experimental results show that combining complementary types of features and increasing codebook size yield high precision for retrieval.
منابع مشابه
Image 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 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 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 کاملبازیابی تعاملی تصاویر طبیعت با بهره گیری از یادگیری چند نمونه ای
Content-based image retrieval (CBIR) has received considerable research interest in the recent years. The basic problem in CBIR is the semantic gap between the high-level image semantics and the low-level image features. Region-based image retrieval and learning from user interaction through relevance feedback are two main approaches to solving this problem. Recently, the research in integra...
متن کامل