Fuzzy Theory in an Image Understanding Retrieval System

1994 ◽  
pp. 215-251 ◽  
Author(s):  
Toshio Norita
Keyword(s):  
Retrieval System ◽  
Fuzzy Theory ◽  
Image Understanding

Design and Evaluation of a Content-Based Image Retrieval System

2011 ◽  
pp. 125-151 ◽  
Author(s):  
David Squire ◽  
Henning Muller ◽  
Wolfgang Muller ◽  
Stephane Marchand-Maillet ◽  
Thierry Pun
Keyword(s):  
Image Retrieval ◽  
Retrieval System ◽  
Image Understanding ◽  
Text Retrieval ◽  
Multimedia Databases ◽  
Multimedia Retrieval ◽  
Context Dependency ◽  
Content Based Image Retrieval ◽  
Classical Text ◽  
Image Retrieval System

The growth in size and accessibility of multimedia databases has changed our approach to information retrieval. Classical text-based systems show their limitations in the context of multimedia retrieval. In this chapter, we address the problem of conceiving and evaluating a content-based image retrieval system. First, we investigate the use of the query-by-example (QBE) paradigm as a base paradigm for the development of a content-based image retrieval system (CBIRS). We show that it should be considered as a complement to the classical textual-based paradigms. We then evaluate the capabilities of the most up-to-date computer vision techniques in contributing to the realisation of such a system. Further, beyond the necessity of accurate image understanding techniques, we show that the amount of the data involved in the process of describing image content should also be considered as an important issue. This aspect of our study is largely based on the experience acquired by the text retrieval (TR) community, which we adapt to the context of CBIR. Similarly, the text retrieval community has also developed significant experience in evaluating retrieval systems, where judgements include subjectivity and context dependency. Extending this experience, we study a coherent framework for performing the evaluation of a CBIRS. As a practical example, we user our Viper CBIR system, using a novel communication protocol called MRML (Multimedia Retrieval Markup Language) to pinpoint the importance of the sharing of resources in facilitating the evaluation and therefore the development of CBIRS.

scholarly journals A human Face Retrieval System Using Linguistic Expression Based on Fuzzy Theory

1994 ◽  
Vol 6 (5) ◽  
pp. 974-983 ◽  
Author(s):  
Makishi NAKAYAMA ◽  
Hiroshi IWAMOTO ◽  
Koji MIYAJIMA ◽  
Toshio NORITA
Keyword(s):  
Retrieval System ◽  
Fuzzy Theory ◽  
Human Face ◽  
Linguistic Expression ◽  
Face Retrieval

Design and Evaluation of a Content-Based Image Retrieval System

2011 ◽  
pp. 38-72
Author(s):  
David Squire ◽  
Henning Muller ◽  
Wolfgang Muller ◽  
Stephane Marchand-Maillet ◽  
Thierry Pun
Keyword(s):  
Image Retrieval ◽  
Retrieval System ◽  
Image Understanding ◽  
Text Retrieval ◽  
Multimedia Databases ◽  
Multimedia Retrieval ◽  
Context Dependency ◽  
Content Based Image Retrieval ◽  
Classical Text ◽  
Image Retrieval System

The growth in size and accessibility of multimedia databases has changed our approach to information retrieval. Classical text-based systems show their limitations in the context of multimedia retrieval. In this chapter, we address the problem of conceiving and evaluating a content-based image retrieval system. First, we investigate the use of the query-by-example (QBE) paradigm as a base paradigm for the development of a content-based image retrieval system (CBIRS). We show that it should be considered as a complement to the classical textual-based paradigms. We then evaluate the capabilities of the most up-to-date computer vision techniques in contributing to the realisation of such a system. Further, beyond the necessity of accurate image understanding techniques, we show that the amount of data involved in the process of describing image content should also be considered as an important issue. This aspect of our study is largely based on the experience acquired by the text retrieval (TR) community, which we adapt to the context of CBIR. Similarly, the text retrieval community has also developed significant experience in evaluating retrieval systems, where judgements include subjectivity and context dependency. Extending this experience, we study a coherent framework for performing the evaluation of a CBIRS. As a practical example, we use our Viper CBIR system, using a novel communication protocol called MRML (Multimedia Retrieval Markup Language) to pinpoint the importance of the sharing of resources in facilitating the evaluation and therefore the development of CBIRS.

Sound-effects Exploratory Retrieval System Based on Various Aspects

2016 ◽  
Vol 136 (12) ◽  
pp. 1712-1720
Author(s):  
Kahori Okamoto ◽  
Ryosuke Yamanishi ◽  
Mitsunori Matsushita
Keyword(s):  
Retrieval System ◽  
Sound Effects

Service Quality Improvement for Airlines by Utilizing QFD and Fuzzy Theory

2014 ◽  
Vol 28 (1) ◽  
pp. 75-98 ◽  
Author(s):  
Eun-Song Bae ◽  
Daecheol Kim
Keyword(s):  
Quality Improvement ◽  
Service Quality ◽  
Fuzzy Theory

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

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