Transportation Informatics Group, ALPEN-ADRIA University of Klagenfurt. Transportation Informatics Group University of Klagenfurt 12/24/2009 1

Transcription

1 Machine Vision Transportation Informatics Group University of Klagenfurt Alireza Fasih, /24/ Address: L4.2.02, Lakeside Park, Haus B04, Ebene 2, Klagenfurt-Austria

2 2D Shape Based Matching Template Matching Gray Level Correlation-Based Matching 12/24/2009 2

3 Template Matching If standard d deviation of the template t image compared to the source image is small enough, template matching may be used. Templates are most often used to identify printed characters, numbers, and other small, simple objects. 12/24/2009 3

4 Method x,y I(x,y) Correlation O(x,y) x,y 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 position. Match is done on a pixel-by-pixel basis. 12/24/2009 4

5 Template Correlation SAD( x, y) = T. Row T. Col i= 0 j= 0 diff ( T. pixle( x + i, y + j), S. pixle( i, j)) Sum of Absolute Difference y res( x, y) = S. Row S. Col x= 0 y= 0 SAD( x, y) x W S. Row S. Col ( x, y ) = x= 0 y= 0 SAD ( x, y ) 12/24/2009 5

6 Template Matching in OpenCV Template Matching Procedure Loading the Search Image Loading the Template Image Making a Result Image Calling the Template Matching Function Finding the Minimum Value in Result Image Drawing a Rectangle 12/24/2009 6

7 Template Matching in OpenCV /* load reference image */ img = cvloadimage( "c:\\image1.bmp bmp", CV_LOAD_IMAGE_COLOR COLOR ); /* load template image */ tpl = cvloadimage( "c:\\tmp1.bmp", CV_LOAD_IMAGE_COLOR ); /* 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 ); /* choose template matching method to be used */ cvmatchtemplate( img, tpl, res, CV_TM_SQDIFF ); cvminmaxloc( res, &minval, &maxval, al &minloc, &maxloc, 0 ); /* draw red rectangle */ cvrectangle( img, cvpoint( minloc.x, minloc.y ), cvpoint( minloc.x + tpl_width, minloc.y + tpl_height ), cvscalar( 0, 0, 255, 0 ), 1, 0, 0 ); 12/24/2009 7

8 Assumptions and Limitationsit ti 1. Template is completely located in source image 2. Partial template matching was not performed (at boundaries, within image) 3. Rotation and scaling will cause poor matches Template Data Set 1 Data Set 2 Data Set 3 Data Set 4 Data Set 5 12/24/2009 8

9 Data Set 1 Correlation Map with Peak Source Image, Found Rectangle, and Correlation Map 12/24/2009 9

10 Data Set 2 Correlation Map with Peak Source Image and Found Rectangle 12/24/

11 Data Set 3 Correlation Map with Peak Source Image and Found Rectangle 12/24/

12 Data Set 4 Correlation Map with Peak Source Image and Found Rectangle 12/24/

13 Data Set 5 Correlation Map with Peak Source Image 12/24/

14 Data Set 5, Result Threshold set to Threshold set to /24/

15 Thank you for your attention 12/24/