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Content-Based Image Retrieval and Feature Extraction: A Comprehensive Review
المؤلفون المشاركون
Ali, Nouman
Ratyal, Naeem
Zafar, Bushra
Latif, Afshan
Rasheed, Aqsa
Sajid, Umer
Ahmed, Jameel
Dar, Saadat Hanif
Sajid, Muhammad
Khalil, Tehmina
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-21، 21ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-08-26
دولة النشر
مصر
عدد الصفحات
21
التخصصات الرئيسية
الملخص EN
Multimedia content analysis is applied in different real-world computer vision applications, and digital images constitute a major part of multimedia data.
In last few years, the complexity of multimedia contents, especially the images, has grown exponentially, and on daily basis, more than millions of images are uploaded at different archives such as Twitter, Facebook, and Instagram.
To search for a relevant image from an archive is a challenging research problem for computer vision research community.
Most of the search engines retrieve images on the basis of traditional text-based approaches that rely on captions and metadata.
In the last two decades, extensive research is reported for content-based image retrieval (CBIR), image classification, and analysis.
In CBIR and image classification-based models, high-level image visuals are represented in the form of feature vectors that consists of numerical values.
The research shows that there is a significant gap between image feature representation and human visual understanding.
Due to this reason, the research presented in this area is focused to reduce the semantic gap between the image feature representation and human visual understanding.
In this paper, we aim to present a comprehensive review of the recent development in the area of CBIR and image representation.
We analyzed the main aspects of various image retrieval and image representation models from low-level feature extraction to recent semantic deep-learning approaches.
The important concepts and major research studies based on CBIR and image representation are discussed in detail, and future research directions are concluded to inspire further research in this area.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Latif, Afshan& Rasheed, Aqsa& Sajid, Umer& Ahmed, Jameel& Ali, Nouman& Ratyal, Naeem…[et al.]. 2019. Content-Based Image Retrieval and Feature Extraction: A Comprehensive Review. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-21.
https://search.emarefa.net/detail/BIM-1200780
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Latif, Afshan…[et al.]. Content-Based Image Retrieval and Feature Extraction: A Comprehensive Review. Mathematical Problems in Engineering No. 2019 (2019), pp.1-21.
https://search.emarefa.net/detail/BIM-1200780
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Latif, Afshan& Rasheed, Aqsa& Sajid, Umer& Ahmed, Jameel& Ali, Nouman& Ratyal, Naeem…[et al.]. Content-Based Image Retrieval and Feature Extraction: A Comprehensive Review. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-21.
https://search.emarefa.net/detail/BIM-1200780
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1200780
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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تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
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