The research described in this paper investigates the rotational robustness of the Viola–Jones algorithm (VJA) object detection method when used for red-winged blackbird (Agelaius phoeniceus) detection. VJA has been successfully used for face detec- tion, but can be adapted to detect a variety of objects. This work uses the histogram of oriented gradients (HOG) descriptor to train the blackbird classifier. Since VJA object detection is inherently not invariant to in-plane object rotation, additional effort is required during training and detection. The proposed method extends the object detection framework developed by Viola and Jones to efficiently handle rotated blackbirds and provide a balance between detection accuracy and computation cost. Keywords Viola–Jones algorithm · Histogram of oriented gradients (HOG) · In-plane object rotation · Region of interest (ROI) · Gradient orientation 1 Introduction commodity. Nationally, blackbird damage to sunflower crops exceeds $13 million dollars. The most limiting factor on the Modern development has been destroying the habitat of production of sunflowers is damage caused by blackbirds, many species, including pest birds, forcing them to rely which generally rank third behind insects and plant spacing more and more on farmed crops for survival, resulting in ; however, blackbirds cannot be easily controlled, unlike crop loss. In Northern
Journal of Real-Time Image Processing – Springer Journals
Published: Jun 4, 2018
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