The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper investigates different methods of representing shape and texture in content-based image retrieval. We have combined five features set in our work and these are trained and classified with SVM (support vector machine) classifier which makes use of machine learning technology. We combined histogram features, texture features (GLCM features), wavelet features, Gabor features, and statistical...
In this research, a new technique For Content Based Image Retrieval (CBIR) with contrast enhancement using multi-feature and multi kernel Support Vector Machine (SVM) method. Color moment (CM), Auto Correlogram (AC), Discrete Wavelet Transform (DWT), Gabor Filter (GF) features are proposed. We extended the previous work which used binary SVM classifier and color features. First of all take a query...
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...
The paper proposes a mobile application for clothing coordination, which could be of great benefit for stores and people seek for fashion advices. The application matches apparel image input with, previously saved apparel images, and then provides the user with the possible matching suggestions based on the apparel outline and dominating colors. For this purpose two Region of Interest (ROI) extraction...
This study is trying to assess methods commonly used in content-based image retrieval (CBIR) for screening mammography analysis. A database consists of 20 different BI-RADS classes of mammogram patches taken from IRMA database is used in this study. Three feature extraction methods, namely grey-level co-occurrence matrix(GLCM), principal component analysis, and scale-invariant feature transform (SIFT)...
RGIRS (Remote Geo-system Image Retrieval System) is a system of retrieving similar image using image features like color feature, texture feature and shape feature. Content based image retrieval system extracts features relevant to query image using feature extraction method. Many RGIRS systems are proposed to retrieve accurate similar image but the problem is no method provides accurate results....
RGIRS (Remote Geo-system Image Retrieval System) is a system of retrieving similar image using image features like color feature, texture feature and shape feature. Content based image retrieval system extracts features relevant to query image using feature extraction method. Many RGIRS systems are proposed to retrieve accurate similar image but the problem is no method provides accurate results....
Content Based Image Retrieval (CBIR) is the task of retrieving the images from the huge set of database on the basis of their own visual content. Content based image recovery is utilized for the programmed indexing and recovery of images depending on the contents of images called as the elements. This paper gives indicated way to utilize these primitive elements to recover the desired image. The procedure...
Automatic image annotation is the process of assigning relevant keywords to the images. It is considered to be potential research area in current scenario. Annotation to an image can be defined as the information which could describe an image by considering three ways i.e. when these images were taken, what are the different objects available in these images and finally the images belongs to whom...
This paper studies about the research on ways to extend and improve query methods for image databases is widespread. we have developed the QBIC (Query by Image Content) system to explore content-based retrieval methods. To achieve the high efficiency and effectiveness of CBIR we are using two type of methods for feature extraction like SVM(support vector machine)and NPRF(navigation-pattern based relevance...
Automatic image annotation is the process by which a computer system automatically assigns metadata in the form of captioning or keywords to a digital image. This application of computer vision technique is used in image retrieval system to organize and locate images of interest from a database. Many techniques have been proposed for image annotation in the last decade that gives reasonable performance...
In this paper we propose the method that extracts the semantic keyword from digital images automatically using color and texture features. The image semantic keyword is widely used in research area like image retrieval, categorization, annotation, management. The method consists of two steps: feature extraction and classification module. In order to extract feature, the image color and PACT (Principal...
Due to the prevalence of digital cameras, it is easy to retrieve digital images from the Internet. With the rapid development of digital image processing, databases, and Internet technologies, how to efficiently manage a large amount of digital images is very important. In this paper, we proposed a novel approach for automatic image annotation. We extract color, texture, and shape features from a...
Flower image retrieval is a significant and challenging problem in content-based image retrieval. We had systematic and overall researches on flower images, including repetitive images filtering, regional segmentation, feature extraction and image retrieval based on SVM, etc. Firstly, in order to ensure retrieval results, we propose a repetitive images detection algorithm based on Canny edge to filter...
In this paper, we propose a new learning method in human motion data analysis. We use Isomap algorithm to reduce high dimensionality of motion's features data. And Support Vector Machine (SVM) for clustering and handling new data. Then data driven decision trees based on multiple instance are automatically constructed to reflect the influence of each point during the comparison of motion similarity...
Pornographic image recognition and filtering are of great significance for web security and content monitoring. In this paper, an adult image recognition method based on support vector machine (SVM) and erotic category is proposed. Global color and texture features and local SIFT feature are extracted to train multiple SVM classifiers for different erotic classes. Face detection is used to filter...
The following topics are dealt with: compressed video indexing; particle swarm optimization; data clustering; image retrieval; video coding; augmented reality; video watermarking; medical image analysis; images fusion; SVM; image segmentation; feature selection; heterogeneous image databases; color texture classification; video surveillance; public transportation; pedestrian detection; Adaboost algorithm;...
Teaching resources are usually massive, complex, hybrid and distributed. In order to search and utilize images from teaching resources with high efficiency, this paper introduced how to use CBIR (Content-based Image Retrieval) to search images from teaching resources, and design a image retrieval system for Teaching resources, it emphasizes on the analysis of relevance feedback algorithm based on...
The following papers are dealt with: software component verification; decision support system; web service; ERP; SQL; semantic data gathering; network security; software development; knowledge-based environmental information system; artificial neural network based radial bending; graph theory model; ontology-based process model; data mining; rough-neuro fuzzy network; feature extraction; query processing;...
Biologically inspired feature (BIF) and its variations have been demonstrated to be effective and efficient for scene classification. It is unreasonable to measure the dissimilarity between two BIFs based on their Euclidean distance. This is because BIFs are extrinsically very high dimensional and intrinsically low dimensional, i.e., BIFs are sampled from a low-dimensional manifold and embedded in...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.