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Integrating fast fourier transformation with constrained independent component analysis for facial image retrieval
العناوين الأخرى
دمج سريع التحول فورييه و مقيدة تحليل المركبات المستقلة لاسترجاع صور الوجه
مقدم أطروحة جامعية
مشرف أطروحة جامعية
أعضاء اللجنة
al-Nihoud, Jihad Quball Awdah
Bani Muhammad, Sad
Slait, Azzam Talal
الجامعة
جامعة آل البيت
الكلية
كلية الأمير الحسين بن عبد الله لتكنولوجيا المعلومات
القسم الأكاديمي
قسم علوم الحاسوب
دولة الجامعة
الأردن
الدرجة العلمية
ماجستير
تاريخ الدرجة العلمية
2013
الملخص الإنجليزي
Content-based image retrieval (CBIR) is a method of searching, browsing, and querying images based on image content.
In this work, we focus on the development of a content-based facial image retrieval technique based on the Constrained Independent Component Analysis (CICA). Recently, Independent Component Analysis (ICA) in reduced Principle Component Analysis (PCA) space is used for characterizing query image.
ICA is used to identify as many ICs as number of observations.
There is an arbitrary ordering of the extracted ICs.
To overcome arbitrary ordering of the extracted ICs, CICA was developed so that only the desired ICs are retrieved. From previous researches, it was found that using PCA with ICA improves the recognition rate.
Therefore, we found it worthwhile to study the effect of using PCA with CICA.
CICA algorithm has some limitations concerning its sensitivity to scale, rotation, and translation.
To overcome the CICA limitations, Fast Fourier Transform (FFT) will be applied on the image before applying CICA. In this work, we aim to study the effect of using edge detection, PCA, and FFT with CICA in content based image retrieval (CBIR) for facial image (as specific domain data).
We suggest four different approaches, using PCA to reduce dimensionality, edge detection to reduce noise, and FFT to overcome some CICA sensitivity problem.
The four approaches are: combing PCA with CICA, perform edge detection then apply PCA and CICA, apply FFT the PCA and CICA, and final approach combines edge detection, FFT, PCA and CICA.
A comparison between the four approaches is performed to specify the recommend approach (the one with heights recognition and retrieving ability).
The comparison between these approaches is from recognition accuracy, average recall and average precision point of views.
The results indicate the effect of FFT2, PCA, and edge detection on the system accuracy.
The experimental results of the proposed CBIR system is tested with public facial databases, the ORL and Yale face database.
The best Recognition accuracy using ORL database is 95.3 %, and the best recognition accuracy using Yale database is 96 %.
By comparing the recognition accuracy of our recommended approach with the accuracy of other works (works that used the same databases), it is evident that our approach outperforms these work.
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الموضوعات
عدد الصفحات
55
قائمة المحتويات
Table of contents.
Abstract.
Chapter One : overview.
Chapter Two : literature survey.
Chapter Three : basic concepts.
Chapter Four : development of the proposed approach.
Chapter Five : experimentation and results analysis.
Chapter Six : conclusion and future work.
References.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Abu Seilik, Umar Awdah Ahmad. (2013). Integrating fast fourier transformation with constrained independent component analysis for facial image retrieval. (Master's theses Theses and Dissertations Master). Al albayt University, Jordan
https://search.emarefa.net/detail/BIM-322006
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Abu Seilik, Umar Awdah Ahmad. Integrating fast fourier transformation with constrained independent component analysis for facial image retrieval. (Master's theses Theses and Dissertations Master). Al albayt University. (2013).
https://search.emarefa.net/detail/BIM-322006
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Abu Seilik, Umar Awdah Ahmad. (2013). Integrating fast fourier transformation with constrained independent component analysis for facial image retrieval. (Master's theses Theses and Dissertations Master). Al albayt University, Jordan
https://search.emarefa.net/detail/BIM-322006
لغة النص
الإنجليزية
نوع البيانات
رسائل جامعية
رقم السجل
BIM-322006
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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