3.2_openCV_blobs

8/12/2019 3.2_openCV_blobs

1/17

Distribution Statement A: Unlimited Distribution

Introduction to Blobs and using the OpenCVBlobs Library

Distribution Statement A: Unlimited Distribution


2/17

OSSIM raining!OV"" Distribution Statement A: Unlimited Distribution

Disclaimer

Though SSC Pacific makes every effort to perform qualityassurance on its training materials, the material in this

presentation may inadvertently include technical inaccuracies orother errors. We would be grateful if users notify us of any errorsor inaccuracies they may find.

The presentation contains references to links and to third partywebsites. These are provided for the convenience and interest ofusers and this implies neither responsibility for, nor approval of,information contained in these websites on the part of the !.S."overnment. The !S" makes no warranty, either e#press orimplied, as to the accuracy, availability or content of information,te#t, graphics in the links$third party websites. The !S" has nottested any software located at these sites and does not makeany representation as to the quality, safety, reliability or suitabilityof such software, nor does this presentation serve to endorse theuse of such sites.

%


3/17


O#er#ie$ o% al&

&verview of 'lob e#traction

(ntroduction to 'lob )ibrary

*#ample+ !sing 'lobs

Conclusions


4/17


O#er#ie$ o% Blob '(traction

(dentify regions in an image that differ inproperties like color or brightness

etect connected regions in binary images !sually done after thresholding

-any different and more comple# algorithms We re going to discuss the

two pass method


5/17


Blob '(traction ) $o*pass algorithm

/elatively easy to understand and implement

0irst pass records equivalences and assigns temporary labels

Second pass replaces temporary labels with the label of its equivalence class

Connectivity checks are carried out by checking the labels of pi#els that are

1orth *ast, 1orth, 1orth West, and West of the current pi#el 0our conditions


6/17



2st condition 3 oes the pi#el to the left 4west5 havethe same value6

7es 8 Same region, assign thesame label to the current pi#el

1o 8 Check ne#t condition

9nd condition 3 o the pi#els to the north and west ofthe current pi#el have the same value but not the samelabel6

7es 8 We know that the north and West

pi#els belong to the same region and must bemerged, assign the current pi#el the minimum ofthe north and west labels and record theirequivalence relationship 1o 8 Check ne#t condition

2,a6

2,a2,6

2,a


7/17



: rd condition 3 oes the pi#el to the left 4west5 have adifferent value and the one to the north the same value6

7es 8 ;ssign the label of the north pi#el tothe current pi#el 1o 8 Check ne#t condition


8/17


;fter the first pass labels are generated for each of the pi#els according to thefour conditions and the equivalence tables are generated


"

+

,

,

-

./ 0

1


9/17


&n the second pass the labels are merged



10/17


>ow do we remove small specks and keep the blobs6 ..?&penC@Threshold;nd*#tract'lobs.cpp

blobs.0ilter4blobs, 'A(1C)! *, C'lob"et;rea45, 'A"/*;T*/, 2==5Bblobs.0ilter4blobs, 'A(1C)! *, C'lob"et-ean45, 'A"/*;T*/, 25B

This allows us to decide how bigD a significant blob is



11/17


1ow only large blobs remain



12/17



2st condition 3 oes the pi#el to the left 4west5 have the same value6 7es 8 Same region, assign the same label to the current pi#el 1o 8 Check ne#t condition

9nd condition 3 o the pi#els to the north and west of the current pi#el havethe same value but not the same label6

7es 8 We know that the north and West pi#els belong to the sameregion and must be merged, assign the current pi#el the minimum of thenorth and west labels and record their equivalence relationship 1o 8 Check ne#t condition

: rd condition 3 oes the pi#el to the left 4west5 have a different value and the

one to the north the same value6 7es 8 ;ssign the label of the north pi#el to the current pi#el 1o 8 Check ne#t condition


13/17


Introduction to Blobs Library %or OpenCV

'lobs )ibrary is a plugin for &penC@. http+$$opencv.willowgarage.com$wiki$cv'lobs)ib

/eplicates functionality of -atlab s 'W)abel and regionprops functions

Takes binary image, and finds all of the blobs. 'lob is a connected obEectD

0or each blob, finds, length, width, and orientation

Can e#tract the sub image corresponding to the blob area

Can filter out blobs below or above a certain2. ;rea9. -ean value


14/17


'(ample: Using the blobs library $ith OpenCV

1ow we ll go through an e#ample using &penC@ and the blobslibrary.

The code is in the folder+..?=:A&penC@AandAblobs?e#amples?'lobsAe#amples?&penC@Threshold;nd*#tract'lobs


15/17


'(ample: Using the blobs library $ith OpenCV

-odify the %.bat files so that the paths are correctbuildAcmakeAproEectAvs2=.batcmakeAarguments.bat

/un buildAcmakeAproEectAvs2=.bat and build the proEect

Compile the proEect in @isual CFF

/un ..? ebug?runProEect.bat


16/17


Blob '(ample 2esults


17/17


Another Sample Image

This simple algorithm can workwith some easyD images

Documents

3.2_openCV_blobs