6 replaced http://mathematica.stackexchange.com/ with https://mathematica.stackexchange.com/ edited Apr 13 '17 at 12:55 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"}]  smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]  corr = ImageCorrelate[large, smaller, EuclideanDistance]; ImageAdjust[corr]  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 ]]  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"}]  smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]  corr = ImageCorrelate[large, smaller, EuclideanDistance]; ImageAdjust[corr]  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 ]]  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"}]  smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]  corr = ImageCorrelate[large, smaller, EuclideanDistance]; ImageAdjust[corr]  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 ]]  5 deleted 15 characters in body edited Jun 7 '16 at 9:57 C. E. 56.1k33 gold badges109109 silver badges222222 bronze badges 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"}]  smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]  corr = ImageCorrelate[large, smaller, EuclideanDistance]; ImageAdjust[corr]  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 ]]  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"}]  smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]  corr = ImageCorrelate[large, smaller, EuclideanDistance]; ImageAdjust[corr]  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 ]]  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"}]  smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]  corr = ImageCorrelate[large, smaller, EuclideanDistance]; ImageAdjust[corr]  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 ]]  4 added 19 characters in body edited Jun 7 '16 at 2:26 C. E. 56.1k33 gold badges109109 silver badges222222 bronze badges 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"}]  smaller = (* subimage manually cropped from the image aboveColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], *)"Grayscale"]  corr = ImageCorrelate[large, smaller, EuclideanDistance]; ImageAdjust[corr]  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 ]]  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"}]  smaller = (* subimage manually cropped from the image above *)  corr = ImageCorrelate[large, smaller, EuclideanDistance]; ImageAdjust[corr]  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 ]]  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"}]  smaller = ColorConvert[Import["http://i.stack.imgur.com/NAHqc.png"], "Grayscale"]  corr = ImageCorrelate[large, smaller, EuclideanDistance]; ImageAdjust[corr]  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 ]]  3 deleted 31 characters in body edited Jun 7 '16 at 2:18 C. E. 56.1k33 gold badges109109 silver badges222222 bronze badges 2 added 69 characters in body edited Jun 6 '16 at 23:23 C. E. 56.1k33 gold badges109109 silver badges222222 bronze badges 1 answered Jun 6 '16 at 23:08 C. E. 56.1k33 gold badges109109 silver badges222222 bronze badges