Saliency detection for content aware computer vision applications
المؤلفون المشاركون
Pandivalavan, Manipoonchelvi
Karuppiah, Muneeswaran
المصدر
The International Arab Journal of Information Technology
العدد
المجلد 14، العدد 4 (31 يوليو/تموز 2017)6ص.
الناشر
تاريخ النشر
2017-07-31
دولة النشر
الأردن
عدد الصفحات
6
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
In recent years, there has been an increased scope for intelligent computer vision systems, which analyse the content of multimedia data.
These systems are expected to process a huge quantum of image/data with high speed and without compromising on effectiveness.
Such systems are benefited by reducing the amount of visual information by selectively processing only a relevant portion of the input data.
The core issue in building these systems is to reduce irrelevant information and retain only a relevant subset of the input visual information.
To address this issue, we propose a region-based computational visual attention model for saliency detection in images.
The proposed model determines the salient object or part of the salient object without prior knowledge of its shape and color.
The proposed framework has three components.
First, the input image is segmented into homogeneous regions and then smaller regions are merged with neighbouring regions based on color and spatial distance between them.
Second, three attributes such as spatial position, color contrast and size of each region are evaluated to distinguish salient object/parts of salient object.
Finally, irrelevant background regions are suppressed and the region level saliency map is generated based on the three attributes.
The generated saliency map preserves the shape and precise location of salient regions and hence it can be used to create high quality segmentation masks for high-level machine vision applications.
Experimental results show that our proposed approach qualitatively better than the state-of-the-art approaches and quantitatively comparable to human perception.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Pandivalavan, Manipoonchelvi& Karuppiah, Muneeswaran. 2017. Saliency detection for content aware computer vision applications. The International Arab Journal of Information Technology،Vol. 14, no. 4.
https://search.emarefa.net/detail/BIM-902695
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Pandivalavan, Manipoonchelvi& Karuppiah, Muneeswaran. Saliency detection for content aware computer vision applications. The International Arab Journal of Information Technology Vol. 14, no. 4 (Jul. 2017).
https://search.emarefa.net/detail/BIM-902695
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Pandivalavan, Manipoonchelvi& Karuppiah, Muneeswaran. Saliency detection for content aware computer vision applications. The International Arab Journal of Information Technology. 2017. Vol. 14, no. 4.
https://search.emarefa.net/detail/BIM-902695
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-902695
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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