یک روش مستقل از تباین برای دودویی‌کردن تصاویر متنی
محورهای موضوعی : مهندسی برق و کامپیوتر
مرتضی ولي‌زاده
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احسان‌اله کبیر
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1 - دانشگاه تربیت مدرس
2 - دانشگاه تربیت مدرس
کلید واژه: آستانهیابی محلی تصاوير متنی آسيب‌ديده مدل جريان آب تخمين روشنايي مستقل از تباین,
چکیده مقاله :
در اين تحقيق يک روش مستقل از تباین برای دودویی‌کردن تصاویر متنی آسیب‌دیده ارائه میشود. این روش به تنظیم پارامتر توسط کاربر نیاز ندارد و برای دودویی‌کردن تصاویر متنی با آسیبهای تباین کم و غیر یکنواختی روشنایی پسزمینه و متن مناسب است. آستانهیابی با روش ارائه‌شده شامل سه مرحله است. در مرحله اول، مستقل از تباین متن و پسزمینه، قسمتهای بارز هر یک از حروف با روش بارش باران اصلاح‌شده استخراج میشود. الگوریتم بارش باران اصلاح‌شده برای استخراج قسمتهای بارز حروف طراحی شده است و مشکلات روش بارش باران را شامل نمیشود. در مرحله دوم با استفاده از نواحی متنی استخراج‌شده، روشنایی نواحی متنی به‌طور محلی تخمین زده میشود. همچنین با توجه به این که در تصاویر متنی تعداد پیکسلهای متن در مقایسه با پیکسلهای پسزمینه ناچیز است، روشنایی پسزمینه با میانگینگیری از روشنایی تصویر اصلی به‌طور محلی تخمین زده میشود. در مرحله سوم برای هر پیکسل، حد آستانه با استفاده از تخمین روشنایی پسزمینه و متن محاسبه میشود. این روش آستانهیابی به‌طور بصری و کمّی با چهار روش متداول آستانهیابی مقایسه شده است و نتایج ارزیابی نشان میدهد که روش پیشنهادی برای دودویی‌کردن تصاویر متنی که با دوربین گرفته شدهاند نسبت به روشهای متداول برتری دارد و نواحی متنی با تباین کم را به خوبی استخراج میکند.
In this paper, we present a contrast independent algorithm for binarization of degraded document images. The proposed algorithm does not require any parameter setting by user. Therefore, it can handle document images with variable foreground and background intensities and low contrast documents. The proposed algorithm involves three consecutive stages. At the first stage, independent of contrast between foreground and background, sensible parts of each character are extracted using the modified water flow model, which is designed for the extraction of sensible part of each character and the drawbacks of water flow model are solved in this algorithm. In the second stage, the gray levels of foreground are estimated using the extracted text pixels and the gray levels of background are locally estimated by averaging the original image. At the third stage, for each pixel of image, the average of estimated foreground and background gray levels is defined as local threshold. After extensive experiments, the proposed binarization algorithm demonstrates superior performance against conventional binarization algorithms on a set of degraded document images captured with camera. Proposed algorithm efficiently extracts the low contrast texts.
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