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Content Based Image Retrieval (CBIR) aims to retrieves images in the database that are similar to a query image based on the contents of the image rather than metadata. The algorithm used to extract features from images is one of the most influential factors towards a CBIR system's performance. In this paper, we take a look at hybrid information descriptors (HID) as the feature extraction algorithm...
Single feature extract method for image retrieval usually cannot get good results and it is hard to find a stable fusion method when across image datasets because the image descriptors usually describe image from single aspect. For this pragmatic issue, an improved FCTH-BoVW feature fusion algorithm called robust FCTH-BoVW is proposed in this paper. Traditional feature fusion methods almost use liner...
Color histogram is an important technique for color image database indexing and retrieving. However, existing color based retrieval techniques are mainly designed for only extracting global or local feature, which cannot provide effective retrieval of images. In this paper, we propose a novel multi-view fusion method for image retrieval by combining the global color with salient regions color feature,...
In this paper, we propose an interactive image retrieval method based on interactive image segmentation and relevance feedback. For testing the performance of the algorithm, we built an image database by web crawlers, and added a background label to each image by histogram analysis. For image retrieval, an interactive image segmentation scheme based on GrabCut has been applied to get the region of...
Color is a significant visual characteristic for both human vision and computer processing. Global color descriptors characterize an image by its color distribution or histogram, and discard information about object location as well as content of different colors. In this paper, we proposed a local color descriptor based on indexed matrix wavelet analysis and fuzzy decision support system (FDSS),...
The automation of image tagging is extremely important research topic in recent years due to its importance in building large image databases. The optimal goal of recent research is to automatically annotate images and overcome the semantic gap between the image content and the associated text representation. Image retrieval from large databases is one of the important domains that can benefit from...
Content-based image retrieval, which is based on the principle of deriving visual similarity based on extracted image features, can be useful, especially since most images are unannotated. However, while almost all images are stored in compressed form (most in JPEG format), the majority of CBIR algorithms operate in the uncompressed pixel domain. This not only leads to a computational overhead for...
Large number of species dan lack of knowledge of Indonesian people about macro-sized Basidiomycota (toadstool) cause identification of those mushrooms become so difficult, so that encouragement to take advantage of the useful mushrooms is still very lacking. The purpose of this research is to propose a method to detect the species of mushrooms that is found around people so that they recognize its...
Image retrieval is an active research area for the last two decades. This area is gaining more importance as the multimedia content over the internet is increasing. Color Texture and shape are the low level image descriptor in Content Based Image Retrieval. These low level image descriptors are used for image representation and retrieval in CBIR. This paper presents a Content Base Image Retrieval...
Environmental Microorganisms (EMs) are very diverse and live in every part of the biosphere (rivers, forests, mountains, etc.), playing critical roles in earth's biogeochemical cycles as they are responsible for the decomposition of waste. Currently, a lot of manual efforts through morphological analysis using microscopes have been put on looking for EMs; however, these methods are expensive and time-consuming...
Image composition is a basic process in digital image editing. Its objective is to enable convenient image object copy-and-paste to generate new images which look natural and realistic. Seamless image composition systems often require users to successively choose a rough region of the inserted object and the target location for automatic which is rather tedious for using 2D input devices like mouse...
Internet trade volumes are rapidly increasing. In this situation, it is becoming increasingly important for online shops owners to have a competitive advantage in their e-commerce shopping services. In this paper, we discuss how such tools as color theory and fuzzy set theory can be applied to e-commerce-oriented image retrieval, more specifically, to online apparel coordination based on customer...
Tongue diagnosis is one of the important topics in the field of Chinese traditional medicine (TCM), and color is the basic element of tongue image, it has important diagnostic value. This paper presents a novel approach to extract color feature of tongue images. First, we use iterative method to extract initial main color and initial number of main color, then we adopt GLA(Generalized Loyd Algorithm)...
Surveillance systems are very important for law enforcement and military applications. Capturing a biometric modality at a distance and under difficult conditions is a very challenging process. While face or gait can be used to identify an individual in such application, tattoos can also help in the identification process whenever available. Tattoos are considered a soft biometric and in some scenarios...
Web image retrieval technology is a hot research topic nowadays, many research institutions at home and abroad are engaged in the research of this topic, and has obtained certain research results. In this paper, at home and abroad about the Web image retrieval technology, on the basis of similarity matching algorithm for image retrieval technique and image analysis and verification. In the Web image...
Under the environment of big data, retrieval becomes a crucial technology and image retrieval is paid more attention and widely used. The paper proposes a second-order retrieval algorithm, of which can be used to retrieval the similar images. Firstly, extracting image sift features. Then, build frequency table of characteristic words by k-means clustering and bag of word algorithm. Finally, based...
Most of the current image retrieval systems for large scale database rely on the Bag-of-Words (BoW) representation and inverted index. We analyze these systems and find that the retrieval performance is largely determined by the discriminative ability of their inverted indexes. This motivates us to combine SIFT and local color features into a two-dimensional inverted index (TD-II). Each dimension...
PORE stands for Photo-Object Recognition based on the Edges. Coincidentally, PORE means to examine something carefully and with due attention, so "we pore over the object layers in search for information about their characteristics with the aim at improving image recognition process". Therefore, this study presents a novel approach to object recognition based on the pattern by using photo...
In the past few years, image retrieval has been one of the hot spots in computer vision field. Among many image retrieval techniques, Bag-of, Word (BoW) model is one of the effective and efficient methods that can search images with visual vocabularies and it is insensitive to massive data and various geometric attacks. But the classical BoW algorithm used some descriptors as its visual words, such...
In this paper we present a new method for content-based searching large image databases by comparing content of a query image and images stored in a database. The algorithm consists of three main steps: feature extraction, indexing and system learning. The feature extraction stage is based on two types of features (SURF keypoints and color). For indexing we use the k-means algorithm and for system...
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