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Обработка изображений и сигналов

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.

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In[2]:=
Click for copyable input
ListAnimate[seq]
Запустить анимацию
Остановить анимацию

Получим средний оптический поток всей видеопоследовательности.

In[3]:=
Click for copyable input
flow = Mean@ImageDisplacements[Append[seq, First[seq]]];
In[4]:=
Click for copyable input
Show[ First[seq], ListVectorPlot[Transpose@Reverse@flow, VectorStyle -> Yellow, VectorPoints -> Fine] ]
Out[4]=

Кривая векторного поля определяет величину присущего вращения.

In[5]:=
Click for copyable input
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"];
In[6]:=
Click for copyable input
curl = ImageAdjust@Image@(listCurl@flow)
Out[6]=

Размытое распределение обеспечивает более надежный результат для крупномасштабных вращений. Черный цвет означает отрицательное вращение; белый цвет означает вращение с положительной ориентацией.

In[7]:=
Click for copyable input
blurredCurl = ImageAdjust[GaussianFilter[curl, 8 {3, 1}]]
Out[7]=

Создадим цветную карту вращения и наложим её поверх исходного изображения.

In[8]:=
Click for copyable input
ImageCompose[seq[[1]], SetAlphaChannel[ Colorize[blurredCurl, ColorFunction -> ColorData[{"TemperatureMap", "Reverse"}]], ColorNegate[blurredCurl]]]
Out[8]=

Родственные примеры

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