1. Recognition system for building flop lines Poojith Jain-0666444

2. Introduction Aim Extraction of informationfrom building flop lines Storing extractedinformation Representinginformation in CityGML

3. BasicConcepts Graph Graph is an ordered pair G: = (V,E) comprising a set V of vertices together with a set E of edges. Graph is used to show connectivity of vertices. Computer Representation of images Pixels Pixel valuebasedon the color Arrayrepresentation

4. The Process Thresholding and NoiseRemoval Labels Identification And image cleaning Graphconstruction Flop line image of Building CityGMLRepresentation

6. Numbersownesrhiprights

8. The Process Thresholding and NoiseRemoval Labels Identification And image cleaning Graphconstruction Flop line image of Building CityGMLRepresentation

9. Thresholding and NoiseRemoval Thresholding Noise Gaps Missing pixels Continuity is important for contour detection Solution ClosingOperation

10. ClosingOperation CLOSING

11. The Process Thresholding and NoiseRemoval Labels Identification And image cleaning Graphconstruction Flop line image of Building CityGMLRepresentation NumberIdentification Removing Labels and Thin Lines

12. OwnershipIdentification Identify the location of the labels Connected component labeling Size criteria Extract the labels Recognize the labels {3,x,y} OCR {4,x,y} OCR

13. The Process Thresholding and NoiseRemoval Labels Identification And image cleaning Graphconstruction Flop line image of Building CityGMLRepresentation NumberIdentification Removing Labels and Thin Lines

14. Removing Labels and Thin Lines Labels indicatepropertyusage and type Thin Lines indicate sub regioninformation Thicklinesindicateboundary Remove labels and thinlines. Connected component labeling Opening operation

15. The Process Thresholding and NoiseRemoval Labels Identification And image cleaning Graphconstruction Flop line image of Building CityGMLRepresentation Skeletonization Corner Dection IdentifyingOwnershipboundary

16. Skeletonization WhySkeletonization? Reducesforegroundregions in an image to a skeleton Bythinningoperation Skeletonshouldbe One pixel width Preserves connectivity Preserves Topology Centered

17. The Process Thresholding and NoiseRemoval Labels Identification And image cleaning Graphconstruction Flop line image of Building CityGMLRepresentation Skeletonization Corner Detection Graphconstruction Face and Floor identification

18. Corner Detection Corenrs are intersection of twoor more edges Corners forms the node of the graph Harris corner Detection Invariant to Scaling Image noise Rotation Illuminationvariance Corner Detection

19. Graph Construction Identify the nodes Identify the edges Optimization

20. Graph Construction Identify the nodes Identify the edges Optimization

21. The Process Thresholding and NoiseRemoval Labels Identification And image cleaning Graphconstruction Flop line image of Building CityGMLRepresentation Skeletonization Corner Detection Graph Construction Face and Floor Identification

22. Face Recognition Eachenclosed face becomesownershipboundary Associateownership Store the information {3,x,y} 3 {4,x,y} 4

23. Floor Identification IdentifyingFloors Storing Information 2 3 4 4 4 1 2 3 4