Обнаружение вращающихся объектов
Функция ImageDisplacements может регистрировать динамические особенности видеопоследовательности. От одного видеокадра к другому, ImageDisplacements обеспечивает векторное поле которое характеризует оптический поток, представляющий собой 2D поле движения объектов в видео.
Анализ векторного поля предоставляет множество инструментов для анализа этих полей движения. Данный пример иллюстрирует использование изогнутого участка вектора для обнаружения вращающихся объектов.
Видеопоследовательность вращающихся ветровых турбин.
seq = {\!\(\*
GraphicsBox[
TagBox[RasterBox[CompressedData["
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"], {{0, 256}, {256, 0}}, {0, 255},
ColorFunction->RGBColor],
BoxForm`ImageTag["Byte", ColorSpace -> "RGB", Interleaving -> True],
Selectable->False],
DefaultBaseStyle->"ImageGraphics",
ImageSizeRaw->{256, 256},
PlotRange->{{0, 256}, {0, 256}}]\), ...};
ListAnimate[seq]
Получим средний оптический поток всей видеопоследовательности.
flow = Mean@ImageDisplacements[Append[seq, First[seq]]];
Show[
First[seq],
ListVectorPlot[Transpose@Reverse@flow, VectorStyle -> Yellow,
VectorPoints -> Fine]
]
Кривая векторного поля определяет величину присущего вращения.
listCurl =
flow \[Function]
ListConvolve[{{0.5`, 0, -0.5`}},
flow[[All, All, 2]], {{1, 2}, {1, 2}}, "Fixed"] -
ListConvolve[{{-0.5`}, {0.`}, {0.5`}},
flow[[All, All, 1]], {{1, 2}, {1, 2}}, "Fixed"];
curl = ImageAdjust@Image@(listCurl@flow)
Размытое распределение обеспечивает более надежный результат для крупномасштабных вращений. Черный цвет означает отрицательное вращение; белый цвет означает вращение с положительной ориентацией.
blurredCurl = ImageAdjust[GaussianFilter[curl, 8 {3, 1}]]
Создадим цветную карту вращения и наложим её поверх исходного изображения.
ImageCompose[seq[[1]],
SetAlphaChannel[
Colorize[blurredCurl,
ColorFunction -> ColorData[{"TemperatureMap", "Reverse"}]],
ColorNegate[blurredCurl]]]