Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Machine VisionMachine VisionTransportation Informatics Group

University of Klagenfurt

Alireza Fasih, 2009

12/24/2009 1Address: L4.2.02, Lakeside Park, Haus B04, Ebene 2, Klagenfurt-Austria

T l t M t hi

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Template Matching2D Shape Based Matching2D Shape Based Matching

12/24/2009 2Gray Level Correlation-Based Matching

T l t M t hi

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Template Matching

If t d d d i ti f th t l t i d t thIf standard deviation of the template image compared to the source image is small enough, template matching may be used.Templates are most often used to identify printed characters, n mbers and other small simple objectsnumbers, and other small, simple objects.

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Method

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Method

x,yI(x,y) O(x,y)

x,yCorrelation

Template Image

Input Image Output Image

The matching process moves the template image to all possible positions in a larger source image and computes a numerical index that indicates how well the template matches the image in that p gposition.

Match is done on a pixel-by-pixel basis.

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Template Correlation

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Template Correlation

RowT ColT

∑ ∑= =

++=RowT

i

ColT

jjipixleSjyixpixleTdiffyxSAD

.

0

.

0)),(.),,(.(),(

RowS ColS. .

∑ ∑= =

=x y

yxSADyxres0 0

),(),(

ySum of Absolute Difference

x

∑ ∑RowS ColS

SADW. .

)()( ∑ ∑= =

=x y

yxSADyxW0 0

),(),(

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T l t M t hi i O CV

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Template Matching in OpenCV

• Template Matching Procedure– Loading the Search Image

Loading the Template Image– Loading the Template Image– Making a Result Image– Calling the Template Matching Functiong p g– Finding the Minimum Value in Result Image– Drawing a Rectangle

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Template Matching in OpenCV

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Template Matching in OpenCV/* load reference image */img = cvLoadImage( "c:\\image1 bmp" CV LOAD IMAGE COLOR );img = cvLoadImage( c:\\image1.bmp , CV_LOAD_IMAGE_COLOR );

/* load template image */tpl = cvLoadImage( "c:\\tmp1.bmp", CV_LOAD_IMAGE_COLOR );

/* t i ' ti *//* get image's properties */img_width = img->width;img_height = img->height;tpl_width = tpl->width;tpl_height = tpl->height;res_width = img_width - tpl_width + 1;res_height = img_height - tpl_height + 1;

/* create new image for template matching computation */res = cvCreateImage( cvSize( res width res height ) IPL DEPTH 32F 1 );res cvCreateImage( cvSize( res_width, res_height ), IPL_DEPTH_32F, 1 );

/* choose template matching method to be used */cvMatchTemplate( img, tpl, res, CV_TM_SQDIFF );

c MinMa Loc( res &min al &ma al &minloc &ma loc 0 )cvMinMaxLoc( res, &minval, &maxval, &minloc, &maxloc, 0 );

/* draw red rectangle */cvRectangle( img, cvPoint( minloc.x, minloc.y ),

cvPoint( minloc.x + tpl_width, minloc.y + tpl_height ),

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cvScalar( 0, 0, 255, 0 ), 1, 0, 0 );

A ti d Li it ti

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Assumptions and Limitations1. Template is completely located in source image1. Template is completely located in source image2. Partial template matching was not performed (at boundaries, within image)3. Rotation and scaling will cause poor matches

TemplateData Set 1 Data Set 2

12/24/2009 8Data Set 3 Data Set 4 Data Set 5

D t S t 1

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Data Set 1

Correlation Map with Peak Source Image, Found Correlation Map with Peak gRectangle, and Correlation Map

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D t S t 2

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Data Set 2

Correlation Map with Peak Source Image and Found Rectangle

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D t S t 3

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Data Set 3

Correlation Map with Peak Source Image and Found Rectangle

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D t S t 4

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Data Set 4

Source Image and FoundCorrelation Map with Peak Source Image and Found Rectangle

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D t S t 5

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Data Set 5

Correlation Map with Peak Source Image

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D t S t 5 R lt

Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Data Set 5, Result

Threshold set to 0.800 Threshold set to 0.200

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Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt

Th k f iThank you for your attention

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