تشخیص درب مبتنی بر بینایی ماشین در صحنههای بیرونی
محورهای موضوعی : عمومىعباس وفایی 1 , مهدی طالبی 2 * , سید امیرحسن منجمی 3
1 - دانشگاه اصفهان
2 - داشجوی دکتری
3 - -
کلید واژه: بینایی کامپیوتر, تشخیص درب, استخراج خطوط, رنگ, بافت,
چکیده مقاله :
دربها نشانه‌ی مهمی جهت ورود و خروج از ساختمان برای افراد نابینا و رباتها میباشند. تشخیص درب در محیطهای بیرونی به یکی از مسایل دشوار در بینایی کامپیوتر تبدیل شده است؛ زیرا معمولا̎ در دربهای محیطهای بیرونی، ویژگیهای یک درب ساده مانند دستگیره، گوشهها و فضای خالی بین درب و زمین آشکار نیستند. در این مقاله، روشی برای تشخیص درب در محیطهای بیرونی ارائه می شود. پس از استخراج خطوط و حذف خطوط اضافی، ناحیه ی بین خطوط عمودی تشکیل میشود و ویژگیهای هر ناحیه شامل ارتفاع، عرض، محل، رنگ، بافت و تعداد خطوط داخل ناحیه استخراج می گردند. سپس از دانش اضافی مانند وجود درب در پایین تصویر، ارتفاع و عرض معقول درب و اختلاف رنگ و بافت درب با ناحیه‌ی اطراف، برای تصمیمگیری وجود درب استفاده می شود. این روش بر روی مجموعه تصاویر eTRIMS و مجموعه تصاویر خودمان شامل دربهای منازل، آپارتمانها و فروشگاهها امتحان شده است و نتایج ارائه‌شده، برتری روش پیشنهادی نسبت به روش‌های پیشین را نشان می‌دهد.
Doors are an important sign for blind people and robots to enter and leave the building. Detection of doors in outdoor environments has become one of the most difficult issues in computer vision; Because usually in outdoor doors, the features of a simple door such as handles, corners and empty space between the door and the floor are not obvious. In this article, a method for detecting doors in outdoor environments is presented. After extracting the lines and removing the extra lines, the area between the vertical lines is formed and the characteristics of each area including height, width, location, color, texture and number of lines inside the area are extracted. Additional knowledge such as the presence of the door at the bottom of the image, the reasonable height and width of the door, and the difference in color and texture of the door with the surrounding area are then used to determine the presence of the door. This method has been tested on our eTRIMS image collection and our image collection, including doors of houses, apartments and shops, and the presented results show the superiority of the proposed method over the previous methods.
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