An enhanced MSER pruning algorithm for detection and localization of Bangla texts from scene images
المؤلفون المشاركون
Islam, Rashedul
Islam, Rafiqul
Talukder, Kamrul
المصدر
The International Arab Journal of Information Technology
العدد
المجلد 17، العدد 3 (31 مايو/أيار 2020)، ص ص. 375-385، 11ص.
الناشر
جامعة الزرقاء عمادة البحث العلمي
تاريخ النشر
2020-05-31
دولة النشر
الأردن
عدد الصفحات
11
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الموضوعات
الملخص EN
Text detection and localization have great importance for content based image analysis and text based image indexing.
The efficiency of text recognition depends on the efficiency of text localization.
So, the main goal of the proposed method is to detect and localize text regions with high accuracy.
To achieve this goal, a new and efficient method has been introduced for localization of Bangla text from scene images.
In order to improve precision and recall as well as f-measure, Maximally Stable Extremal Region (MSER) based method along with double filtering techniques have been used.
As MSER algorithm generates many false positives, we have introduced double filtering method for removing these false positives to increase the f-measure to a great extent.
Our proposed method works at three basic levels.
Firstly, MSER regions are generated from the input color image by converting it into gray scale image.
Secondly, some heuristic features are used to filter out most of the false positives or non-text regions.
Lastly, Stroke Width Transform (SWT) based filtering method is used to filter out remaining non-text regions.
Remaining components are then grouped into candidate text regions marked by bounding box over each region.
As there is no benchmark database for Bangla text, the proposed method is implemented on our own prepared database consisting of 200 scene images of Bangla texts and has got prominent performance.
To evaluate the performance of our proposed approach, we have also tested the proposed method on International Conference on Document Analysis and Recognition( ICDAR) 2013 benchmark database and have got a better result than the related existing methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Islam, Rashedul& Islam, Rafiqul& Talukder, Kamrul. 2020. An enhanced MSER pruning algorithm for detection and localization of Bangla texts from scene images. The International Arab Journal of Information Technology،Vol. 17, no. 3, pp.375-385.
https://search.emarefa.net/detail/BIM-962350
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Islam, Rashedul…[et al.]. An enhanced MSER pruning algorithm for detection and localization of Bangla texts from scene images. The International Arab Journal of Information Technology Vol. 17, no. 3 (May. 2020), pp.375-385.
https://search.emarefa.net/detail/BIM-962350
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Islam, Rashedul& Islam, Rafiqul& Talukder, Kamrul. An enhanced MSER pruning algorithm for detection and localization of Bangla texts from scene images. The International Arab Journal of Information Technology. 2020. Vol. 17, no. 3, pp.375-385.
https://search.emarefa.net/detail/BIM-962350
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 383-385
رقم السجل
BIM-962350
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