In this paper, we conduct research on the multimedia information retrieval algorithm based on the information restructuring and image reconstruction. With the massive growth of information resources, people through va...In this paper, we conduct research on the multimedia information retrieval algorithm based on the information restructuring and image reconstruction. With the massive growth of information resources, people through various retrieval tools for too much information, led directly to information overload. In vector space model and probability retrieval model based on information retrieval tools rarely consider the user＇ s personalized information needs and features, has resulted in a large amount of information retrieval result and correlation information the user＇ s information demand is not big. In order to improve the existing retrieval system, in recent years, scholars to study looked that context information retrieval context factors need to be considered, such as the retrieval time, place and the interactive history, mission, environment and other factors stated or implied in the retrieval process. At present, the context research has become the information behavior, information search process and the research hotspot in the field of information retrieval interaction.展开更多
<div style="text-align:justify;"> Digital image collection as rapidly increased along with the development of computer network. Image retrieval system was developed purposely to provide an efficient to...<div style="text-align:justify;"> Digital image collection as rapidly increased along with the development of computer network. Image retrieval system was developed purposely to provide an efficient tool for a set of images from a collection of images in the database that matches the user’s requirements in similarity evaluations such as image content similarity, edge, and color similarity. Retrieving images based on the content which is color, texture, and shape is called content based image retrieval (CBIR). The content is actually the feature of an image and these features are extracted and used as the basis for a similarity check between images. The algorithms used to calculate the similarity between extracted features. There are two kinds of content based image retrieval which are general image retrieval and application specific image retrieval. For the general image retrieval, the goal of the query is to obtain images with the same object as the query. Such CBIR imitates web search engines for images rather than for text. For application specific, the purpose tries to match a query image to a collection of images of a specific type such as fingerprints image and x-ray. In this paper, the general architecture, various functional components, and techniques of CBIR system are discussed. CBIR techniques discussed in this paper are categorized as CBIR using color, CBIR using texture, and CBIR using shape features. This paper also describe about the comparison study about color features, texture features, shape features, and combined features (hybrid techniques) in terms of several parameters. The parameters are precision, recall and response time. </div>展开更多
In medical research and clinical diagnosis, automated or computer-assisted classification and retrieval methods are highly desirable to offset the high cost of manual classification and manipulation by medical experts...In medical research and clinical diagnosis, automated or computer-assisted classification and retrieval methods are highly desirable to offset the high cost of manual classification and manipulation by medical experts. To facilitate the decision-making in the health-care and the related areas, in this paper, a two-step content-based medical image retrieval algorithm is proposed. Firstly, in the preprocessing step, the image segmentation is performed to distinguish image objects, and on the basis of the ...展开更多
Cloth image retrieval in E-Commerce is a challenging task. In this paper, we propose an effective approach to solve this problem. Our work chooses three features for retrieval: (1) description (2) category (3) color f...Cloth image retrieval in E-Commerce is a challenging task. In this paper, we propose an effective approach to solve this problem. Our work chooses three features for retrieval: (1) description (2) category (3) color features. It can handle clothes with multiple colors, complex background, and model disturbances. To evaluate the proposed method, we collect a set of women cloth images from Amazon.com. Results reported here demonstrate the robustness and effectiveness of our retrieval method.展开更多
The information work in the hospital is very complicated. The amount of data is huge, and the forms are various. It is very troublesome to organize and find the data you need. In order to solve the problem, which ofte...The information work in the hospital is very complicated. The amount of data is huge, and the forms are various. It is very troublesome to organize and find the data you need. In order to solve the problem, which often appears in the process of analyzing medical case and data, we use Labview2017 to design the corresponding multimedia data calling system for the purpose of rapid searching and effective extraction. This program, which greatly improves work efficiency, can realize fast searching multimedia data in the folder. Since we use of this type of system, the work efficiency has been greatly improved, and the burden on the staff has been greatly reduced.展开更多
文摘In this paper, we conduct research on the multimedia information retrieval algorithm based on the information restructuring and image reconstruction. With the massive growth of information resources, people through various retrieval tools for too much information, led directly to information overload. In vector space model and probability retrieval model based on information retrieval tools rarely consider the user＇ s personalized information needs and features, has resulted in a large amount of information retrieval result and correlation information the user＇ s information demand is not big. In order to improve the existing retrieval system, in recent years, scholars to study looked that context information retrieval context factors need to be considered, such as the retrieval time, place and the interactive history, mission, environment and other factors stated or implied in the retrieval process. At present, the context research has become the information behavior, information search process and the research hotspot in the field of information retrieval interaction.
文摘<div style="text-align:justify;"> Digital image collection as rapidly increased along with the development of computer network. Image retrieval system was developed purposely to provide an efficient tool for a set of images from a collection of images in the database that matches the user’s requirements in similarity evaluations such as image content similarity, edge, and color similarity. Retrieving images based on the content which is color, texture, and shape is called content based image retrieval (CBIR). The content is actually the feature of an image and these features are extracted and used as the basis for a similarity check between images. The algorithms used to calculate the similarity between extracted features. There are two kinds of content based image retrieval which are general image retrieval and application specific image retrieval. For the general image retrieval, the goal of the query is to obtain images with the same object as the query. Such CBIR imitates web search engines for images rather than for text. For application specific, the purpose tries to match a query image to a collection of images of a specific type such as fingerprints image and x-ray. In this paper, the general architecture, various functional components, and techniques of CBIR system are discussed. CBIR techniques discussed in this paper are categorized as CBIR using color, CBIR using texture, and CBIR using shape features. This paper also describe about the comparison study about color features, texture features, shape features, and combined features (hybrid techniques) in terms of several parameters. The parameters are precision, recall and response time. </div>
文摘In medical research and clinical diagnosis, automated or computer-assisted classification and retrieval methods are highly desirable to offset the high cost of manual classification and manipulation by medical experts. To facilitate the decision-making in the health-care and the related areas, in this paper, a two-step content-based medical image retrieval algorithm is proposed. Firstly, in the preprocessing step, the image segmentation is performed to distinguish image objects, and on the basis of the ...
文摘Cloth image retrieval in E-Commerce is a challenging task. In this paper, we propose an effective approach to solve this problem. Our work chooses three features for retrieval: (1) description (2) category (3) color features. It can handle clothes with multiple colors, complex background, and model disturbances. To evaluate the proposed method, we collect a set of women cloth images from Amazon.com. Results reported here demonstrate the robustness and effectiveness of our retrieval method.
文摘The information work in the hospital is very complicated. The amount of data is huge, and the forms are various. It is very troublesome to organize and find the data you need. In order to solve the problem, which often appears in the process of analyzing medical case and data, we use Labview2017 to design the corresponding multimedia data calling system for the purpose of rapid searching and effective extraction. This program, which greatly improves work efficiency, can realize fast searching multimedia data in the folder. Since we use of this type of system, the work efficiency has been greatly improved, and the burden on the staff has been greatly reduced.
