A Study on Efficient Feature-Vector Extraction for Content-Based Image Retrieval System

التفاصيل البيبلوغرافية
العنوان: A Study on Efficient Feature-Vector Extraction for Content-Based Image Retrieval System
المؤلفون: Gi Hyoung Yoo, Hoon Sung Kwak
المصدر: The KIPS Transactions:PartB. :309-314
بيانات النشر: Korea Information Processing Society, 2006.
سنة النشر: 2006
مصطلحات موضوعية: Automatic image annotation, Computer science, Feature (computer vision), Feature vector, Top-hat transform, Data mining, Visual Word, computer.software_genre, Content-based image retrieval, computer, Image retrieval, Feature detection (computer vision)
الوصف: Recently, multimedia DBMS is appeared to be the core technology of the information society to store, manage and retrieve multimedia data efficiently. In this paper, we propose a new method for content based-retrieval system using wavelet transform, energy value to extract automatically feature vector from image data, and suggest an effective retrieval technique through this method. Wavelet transform is widely used in image compression and digital signal analysis, and its coefficient values reflect image feature very well. The correlation in wavelet domain between query image data and the stored data in database is used to calculate similarity. In order to assess the image retrieval performance, a set of hundreds images are run. The method using standard derivation and mean value used for feature vector extraction are compared with that of our method based on energy value. For the simulation results, our energy value method was more effective than the one using standard derivation and mean value.
تدمد: 1598-284X
DOI: 10.3745/kipstb.2006.13b.3.309
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::e87a56b912c83acd1cc664d593aeaf28
https://doi.org/10.3745/kipstb.2006.13b.3.309
Rights: OPEN
رقم الانضمام: edsair.doi...........e87a56b912c83acd1cc664d593aeaf28
قاعدة البيانات: OpenAIRE
الوصف
تدمد:1598284X
DOI:10.3745/kipstb.2006.13b.3.309