The Orange Objects Classification. My process Get the image from the robot Mark the position of the ball in each image Calculate all 7 attributes –Width.

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Presentation transcript:

The Orange Objects Classification

My process Get the image from the robot Mark the position of the ball in each image Calculate all 7 attributes –Width –Height –Area –Perimeter –Form Factor –Distance –Eigen Value

Original Image

Mark the position of the ball

HUE color model

Orange objects in HUE

Discard Big objects

Find interested attribute Width, Height, and Area Width Height Area

Perimeter = ( * # of Diagonal lines) + # of Straight lines From this image: # of Diagonal line = 45 lines # of Straight line = 80 lines Perimeter = Find interested attributes

Perimeter = 18* +28 = WHAPFF.EigDist.APFF.EigDist.

Find interested attributes Form Factor (FF.) = where A = area, and P = perimeter If FF. is or close to 1  the circle object

Form Factor (FF.) BlueYellow Area121 Perim.4044 FF

How to calculate the perimeter

= 1 diagonal line and 1 straight line

= 1 diagonal line

= 2 diagonal lines

= 1 straight line

= 2 straight lines

Old Eigen Value We set the threshold value as EigVal 1 > (0.75*EigVal 2 )  It’s a ball

New Eigen Value (let C4.5 learn it) Eigen Value ratio (Eig) Eig = 1 st Eigen value / 2 nd Eigen value Eig

Find interested attributes Centroids and Distance

C4.5 result 1 st combination 2 nd combination New training DataNew test Data Training DataTest Data

Decision tree (7 attributes) size after pruning: 59 nodes <= > <=29>29 >14 <= <=0.4753> <=0.7965> <=64>64 <=0.5609>0.5609<=4468 >4468 <= > <=10 >10 <=0.8379> >13<=13 <=14 <=0.8812> > <= <=0.5262> <=0.6013> > <=16>16 <= > >0.9053<= > <= <=9>9 <= > <=13>13 >85<=85 <=80>80 <= > <= > <= >

Conclusion Gained more experiment with machine learning, C4.5 More practice with Matlab

Perimeter = 18* +28 = WHAPFF.EigDist.APFF.EigDist.

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