scholarly journals An Intelligent Web Digital Image Metadata Service Platform for Social Curation Commerce Environment

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Seong-Yong Hong ◽  
Sung-Joon Lee
Keyword(s):  
Knowledge Management ◽  
Information Retrieval ◽  
Digital Image ◽  
Image Data ◽  
Multimedia Databases ◽  
Multimedia Data ◽  
Shopping Mall ◽  
Global Features ◽  
Image Information ◽  
Image Metadata

Information management includes multimedia data management, knowledge management, collaboration, and agents, all of which are supporting technologies for XML. XML technologies have an impact on multimedia databases as well as collaborative technologies and knowledge management. That is, e-commerce documents are encoded in XML and are gaining much popularity for business-to-business or business-to-consumer transactions. Recently, the internet sites, such as e-commerce sites and shopping mall sites, deal with a lot of image and multimedia information. This paper proposes an intelligent web digital image information retrieval platform, which adopts XML technology for social curation commerce environment. To support object-based content retrieval on product catalog images containing multiple objects, we describe multilevel metadata structures representing the local features, global features, and semantics of image data. To enable semantic-based and content-based retrieval on such image data, we design an XML-Schema for the proposed metadata. We also describe how to automatically transform the retrieval results into the forms suitable for the various user environments, such as web browser or mobile device, using XSLT. The proposed scheme can be utilized to enable efficient e-catalog metadata sharing between systems, and it will contribute to the improvement of the retrieval correctness and the user’s satisfaction on semantic-based web digital image information retrieval.

New digital image processing technology for FSEM microscopy

1993 ◽  
Vol 51 ◽  
pp. 212-213
Author(s):  
Klaus-Ruediger Peters ◽  
Eisaku Oho
Keyword(s):  
Digital Image ◽  
Image Data ◽  
Data Set ◽  
Raw Data ◽  
Image Information ◽  
Visual Access ◽  
Spatial Dimensions ◽  
Image Detail ◽  
Detail Enhancement ◽  
Image Details

Digital image acquisition and processing can provide many advantages over conventional analog image information handling, i.e., undisturbed access to the “raw data set”, quantitative analysis of the image information, and reduced costs and increased flexibility of image data handling. However, it may principally change microscopy by providing a new facility for instant exhaustive data presentation in acquired images. Detail imaging is one of the basic microscopic tasks but visual access to detail information is cumbersome and often left to post-session data analysis. A dedicated software/hardware technique is now available for automatic “near-real-time” enhancement of image detail information visually not accessible in the “raw data” image. Pertinent image details include spatial dimensions of only a few pixels in size (spatial details) and intensity variations of only a few intensity steps in height (intensity details). While conventional image enhancement techniques often produce serious image artifacts which exclude a closer inspection of enhanced detail information, the new pixel-accurate processing (PAP) technology allows instant image evaluation at an accuracy-level of the raw data through detail enhancement in full-frame images, digital zoom and noise smoothing.

scholarly journals Application of content based image retrieval in digital image search system

2021 ◽  
Vol 10 (2) ◽  
pp. 1122-1128
Author(s):  
Syamsul Yakin ◽  
Tasrif Hasanuddin ◽  
Nia Kurniati
Keyword(s):  
Image Retrieval ◽  
Digital Image ◽  
Image Data ◽  
Multimedia Data ◽  
Content Based Image Retrieval ◽  
Discrete Wavelet ◽  
Image Search ◽  
Image Description ◽  
Search System ◽  
Query Image

Multimedia data is growing rapidly in the current digital era, one of which is digital image data. The increasing need for a large number of digital image datasets makes the constraints faced eventually drain a lot of time and cause the process of image description to be inconsistent. Therefore, a method is needed in processing the data, especially in searching digital image data in large image dataset to find image data that are relevant to the query image. One of the proposed methods for searching information based on image content is content based image retrieval (CBIR). The main advantage of the CBIR method is automatic retrieval process, compared to traditional keyword. This research was conducted on a combination of the HSV color histogram methods and the discrete wavelet transform to extract color features and textures features, while the chi-square distance technique was used to compare the test images with images into a database. The results have showed that the digital image search system with color and texture features have a precision value of 37.5% - 100%, with an average precision value of 80.71%, while the percentage accuracy is 93.7% - 100% with an average accuracy is 98.03%.

Pencarian File Gambar Berdasarkan Dominasi Warna

2011 ◽  
Vol 2 (1) ◽  
Author(s):  
Vina Chovan Epifania ◽  
Eko Sediyono
Keyword(s):  
Digital Image ◽  
Retrieval System ◽  
Color Image ◽  
Color Space ◽  
Image Data ◽  
Image Search ◽  
Test Results ◽  
Application Form ◽  
Space Model ◽  
Image File

Abstract. Image File Searching Based on Color Domination. One characteristic of an image that can be used in image searching process is the composition of the colors. Color is a trait that is easily seen by man in the picture. The use of color as a searching parameter can provide a solution in an easier searching for images stored in computer memory. Color images have RGB values that can be computed and converted into HSL color space model. Use of HSL images model is very easy because it can be calculated using a percent, so that in each pixel of the image can be grouped and named, this can give a dominant values of the colors contained in one image. By obtaining these values, the image search can be done quickly just by using these values to a retrieval system image file. This article discusses the use of the HSL color space model to facilitate the searching for a digital image in the digital image data warehouse. From the test results of the application form, a searching is faster by using the colors specified by the user. Obstacles encountered were still searching with a choice of 15 basic colors available, with a limit of 33% dominance of the color image search was not found. This is due to the dominant color in each image has the most dominant value below 33%.   Keywords: RGB, HSL, image searching Abstrak. Salah satu ciri gambar yang dapat dipergunakan dalam proses pencarian gambar adalah komposisi warna. Warna adalah ciri yang mudah dilihat oleh manusia dalam citra gambar. Penggunaan warna sebagai parameter pencarian dapat memberikan solusi dalam memudahkan pencarian gambar yang tersimpan dalam memori komputer. Warna gambar memiliki nilai RGB yang dapat dihitung dan dikonversi ke dalam model HSL color space. Penggunaan model gambar HSL sangat mudah karena dapat dihitung dengan menggunakan persen, sehingga dalam setiap piksel gambar dapat dikelompokan dan diberi nama, hal ini dapat memberikan suatu nilai dominan dari warna yang terdapat dalam satu gambar. Dengan diperolehnya nilai tersebut, pencarian gambar dapat dilakukan dengan cepat hanya dengan menggunakan nilai tersebut pada sistem pencarian file gambar. Artikel ini membahas tentang penggunaan model HSL color space untuk mempermudah pencarian suatu gambar digital didalam gudang data gambar digital. Dari hasil uji aplikasi yang sudah dibuat, diperoleh pencarian yang lebih cepat dengan menggunakan pilihan warna yang ditentukan sendiri oleh pengguna. Kendala yang masih dijumpai adalah pencarian dengan pilihan 15 warna dasar yang tersedia, dengan batas dominasi warna 33% tidak ditemukan gambar yang dicari. Hal ini disebabkan warna dominan disetiap gambar kebanyakan memiliki nilai dominan di bawah 33%. Kata Kunci: RGB, HSL, pencarian gambar

CIKM 2020 conference report

2021 ◽  
pp. 1-4
Author(s):  
Mathieu D'Aquin ◽  
Stefan Dietze
Keyword(s):  
United States ◽  
Machine Learning ◽  
Knowledge Management ◽  
Information Retrieval ◽  
Conference Report ◽  
The United States ◽  
Knowledge Based ◽  
The World ◽  
Science Conference ◽  
Information And Knowledge Management

The 29th ACM International Conference on Information and Knowledge Management (CIKM) was held online from the 19 th to the 23 rd of October 2020. CIKM is an annual computer science conference, focused on research at the intersection of information retrieval, machine learning, databases as well as semantic and knowledge-based technologies. Since it was first held in the United States in 1992, 28 conferences have been hosted in 9 countries around the world.

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