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The most straightforward approach is ImageCorrelate. I'll show you an example. nikie wrote an excellent answer explaining this method herehere.

large = ExampleData[{"TestImage", "Boat"}]

Mathematica graphics

smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]

Mathematica graphics

corr = ImageCorrelate[large, smaller, EuclideanDistance];
ImageAdjust[corr]

Mathematica graphics

The minimum – the blackest area – is the best match between the smaller image and the larger image.

min = PixelValuePositions[corr, "Min"] // First;
HighlightImage[
 large, Rectangle[
  min - ImageDimensions[smaller]/2,
  min + ImageDimensions[smaller]/2
  ]]

Mathematica graphics

The most straightforward approach is ImageCorrelate. I'll show you an example. nikie wrote an excellent answer explaining this method here.

large = ExampleData[{"TestImage", "Boat"}]

Mathematica graphics

smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]

Mathematica graphics

corr = ImageCorrelate[large, smaller, EuclideanDistance];
ImageAdjust[corr]

Mathematica graphics

The minimum – the blackest area – is the best match between the smaller image and the larger image.

min = PixelValuePositions[corr, "Min"] // First;
HighlightImage[
 large, Rectangle[
  min - ImageDimensions[smaller]/2,
  min + ImageDimensions[smaller]/2
  ]]

Mathematica graphics

The most straightforward approach is ImageCorrelate. I'll show you an example. nikie wrote an excellent answer explaining this method here.

large = ExampleData[{"TestImage", "Boat"}]

Mathematica graphics

smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]

Mathematica graphics

corr = ImageCorrelate[large, smaller, EuclideanDistance];
ImageAdjust[corr]

Mathematica graphics

The minimum – the blackest area – is the best match between the smaller image and the larger image.

min = PixelValuePositions[corr, "Min"] // First;
HighlightImage[
 large, Rectangle[
  min - ImageDimensions[smaller]/2,
  min + ImageDimensions[smaller]/2
  ]]

Mathematica graphics

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The most straightforward approach is ImageCorrelate. I'll show you an example. nikie wrote an excellent answer explaining this method here.

large = ExampleData[{"TestImage", "Boat"}]

Mathematica graphics

smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]

Mathematica graphics

corr = ImageCorrelate[large, smaller, EuclideanDistance];
ImageAdjust[corr]

Mathematica graphics

The minimum – the blackest area – is the best match between the smaller image and the larger image.

min = PixelValuePositions[corr, Min[ImageData[corr]]]"Min"] // First;
HighlightImage[
 large, Rectangle[
  min - ImageDimensions[smaller]/2,
  min + ImageDimensions[smaller]/2
  ]]

Mathematica graphics

The most straightforward approach is ImageCorrelate. I'll show you an example. nikie wrote an excellent answer explaining this method here.

large = ExampleData[{"TestImage", "Boat"}]

Mathematica graphics

smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]

Mathematica graphics

corr = ImageCorrelate[large, smaller, EuclideanDistance];
ImageAdjust[corr]

Mathematica graphics

The minimum – the blackest area – is the best match between the smaller image and the larger image.

min = PixelValuePositions[corr, Min[ImageData[corr]]] // First;
HighlightImage[
 large, Rectangle[
  min - ImageDimensions[smaller]/2,
  min + ImageDimensions[smaller]/2
  ]]

Mathematica graphics

The most straightforward approach is ImageCorrelate. I'll show you an example. nikie wrote an excellent answer explaining this method here.

large = ExampleData[{"TestImage", "Boat"}]

Mathematica graphics

smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]

Mathematica graphics

corr = ImageCorrelate[large, smaller, EuclideanDistance];
ImageAdjust[corr]

Mathematica graphics

The minimum – the blackest area – is the best match between the smaller image and the larger image.

min = PixelValuePositions[corr, "Min"] // First;
HighlightImage[
 large, Rectangle[
  min - ImageDimensions[smaller]/2,
  min + ImageDimensions[smaller]/2
  ]]

Mathematica graphics

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The most straightforward approach is ImageCorrelate. I'll show you an example. nikie wrote an excellent answer explaining this method here.

large = ExampleData[{"TestImage", "Boat"}]

Mathematica graphics

smaller = (* subimage manually cropped from the image aboveColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], *)"Grayscale"]

Mathematica graphics

corr = ImageCorrelate[large, smaller, EuclideanDistance];
ImageAdjust[corr]

Mathematica graphics

The minimum – the blackest area – is the best match between the smaller image and the larger image.

min = PixelValuePositions[corr, Min[ImageData[corr]]] // First;
HighlightImage[
 large, Rectangle[
  min - ImageDimensions[smaller]/2,
  min + ImageDimensions[smaller]/2
  ]]

Mathematica graphics

The most straightforward approach is ImageCorrelate. I'll show you an example. nikie wrote an excellent answer explaining this method here.

large = ExampleData[{"TestImage", "Boat"}]

Mathematica graphics

smaller = (* subimage manually cropped from the image above *)

Mathematica graphics

corr = ImageCorrelate[large, smaller, EuclideanDistance];
ImageAdjust[corr]

Mathematica graphics

The minimum – the blackest area – is the best match between the smaller image and the larger image.

min = PixelValuePositions[corr, Min[ImageData[corr]]] // First;
HighlightImage[
 large, Rectangle[
  min - ImageDimensions[smaller]/2,
  min + ImageDimensions[smaller]/2
  ]]

Mathematica graphics

The most straightforward approach is ImageCorrelate. I'll show you an example. nikie wrote an excellent answer explaining this method here.

large = ExampleData[{"TestImage", "Boat"}]

Mathematica graphics

smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]

Mathematica graphics

corr = ImageCorrelate[large, smaller, EuclideanDistance];
ImageAdjust[corr]

Mathematica graphics

The minimum – the blackest area – is the best match between the smaller image and the larger image.

min = PixelValuePositions[corr, Min[ImageData[corr]]] // First;
HighlightImage[
 large, Rectangle[
  min - ImageDimensions[smaller]/2,
  min + ImageDimensions[smaller]/2
  ]]

Mathematica graphics

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