کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
84174 158868 2015 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Detecting citrus fruits and occlusion recovery under natural illumination conditions
ترجمه فارسی عنوان
تشخیص میوه های مرکبات و بازیابی اکلوژن در شرایط نور طبیعی
کلمات کلیدی
شرایط نور طبیعی، میوه های خانواده مرکبات، تشخیص بازیابی عذاب رابطه نظم جزئی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


• A method based on contour fragments was developed to detect fruits in tree canopy.
• This method can detect citrus fruits even with highlights and shades on surface.
• The integrated contour of fruits can be recovered from their fragments.
• The partial order relations between overlapped fruits were derived.
• The fitting error and time performance were discussed.

A method based on color information and contour fragments was developed to identify citrus fruits in variable illumination conditions within tree canopy, in order to guide the robots for harvesting citrus fruits. The color properties of fruit targets within citrus-grove scene were analyzed, a preliminary segmentation method was put forward by fusing the chromatic aberration information and normalized RGB model. The set of contour fragments was constructed by detecting the significant edges of chromatic aberration map and the corners within these edges. The valid subset was chosen out by three indicators of every fragment: length, bending degree, and concavity or convexity. The combination analysis was done for these valid contour fragments, and the ellipse fitting was used for every subset of valid fragments to recover the occluded fruits. The partial order relationship was derived based on the distribution of the edge within the overlapped area. The results showed that occluded fruits were effectively recovered under natural outdoor light conditions using the proposed method, and the relative error was 5.27%. The partial order relation of fruit targets provide key cues for path planning of harvesting robot.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 110, January 2015, Pages 121–130
نویسندگان
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