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The project your are working on is not really a pet project and it is hard enough!:)

I recommend to go over these articles to some works in aerial vision:
ECCV_workshop
But a here I explain an intuitive way for this special problem:
1. You have color cues [Green], so extract the green channel and do a color segmentation using watershed algorithm followed by a Connected Component (an Opencv example here). The find the area and bounding box area and they should approximate each other. So trees and green non court areas will be removed.
2. For finding court lines, isolate white pixcels(approx. R=G=b).

The project your are working on is not really a pet project and it is hard enough!:)

I recommend to go over these articles the workshop site address to some works new approaches in aerial vision:
ECCV_workshop
But a here I explain an intuitive way for this special problem:
1. You have color cues [Green], so extract the green channel and do a color segmentation using watershed algorithm followed by a Connected Component (an Opencv example here). The find the area and bounding box area and they should approximate each other. So trees and green non court areas will be removed.
2. For finding court lines, isolate white pixcels(approx. R=G=b).R=G=B).

The project your are working on is not really a pet project and it is hard enough!:)

I recommend to go over the workshop site to address to some new approaches in aerial vision:
ECCV_workshop
But a here I explain an intuitive way for this special problem:
1. You have color cues [Green], so extract the green channel and do a color segmentation using watershed algorithm followed by a Connected Component (an Opencv example here). The find the area and bounding box area and they should approximate each other. So trees and green non court areas will be removed.
2. For finding court lines, isolate white pixcels(approx. R=G=B).

The project your are working on is not really a pet project and it is hard enough!:)

I recommend to go over the workshop site to address some new approaches in aerial vision:
ECCV_workshop
But a here I explain an intuitive way for this special problem:
1. You have color cues [Green], so extract the green channel and do a color segmentation using watershed algorithm followed by a Connected Component (an Opencv example here). The find the area and bounding box area and they should approximate each other. So trees and green non court areas will be removed.
2. For finding court lines, isolate white pixcels(approx. R=G=B).

The project your are working on is not really a pet project and it is hard enough!:)

I recommend to go over the workshop site to address some new approaches in aerial vision:
ECCV_workshop
But a here I explain an intuitive way for this special problem:
1. You have color cues [Green], so extract the green channel and do a color segmentation using watershed algorithm followed by a Connected Component (an Opencv example here). The find the area and bounding box area and they should approximate each other. So trees and green non court areas will be removed.
2. For finding court lines, isolate white pixcels(approx. R=G=B).

The project your are working on is not really a pet project and it is hard enough!:)

I recommend to go over the workshop site to address some new approaches in aerial vision:
ECCV_workshop
But a here I explain an intuitive way for this special problem:
1. You have color cues [Green], so extract the green channel and do a color segmentation using watershed algorithm followed by a Connected Component (an Opencv example here). The Then find the area and bounding box area of remaining connected components and they should approximate each other. So trees and green non court areas will be removed.
2. For finding court lines, isolate white pixcels(approx. R=G=B).