Symbol Representation in Map Image Compression UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE FINLAND Alexander Akimov and Pasi Fränti ACM Symposium.

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Presentation transcript:

Symbol Representation in Map Image Compression UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE FINLAND Alexander Akimov and Pasi Fränti ACM Symposium on Applied Computing (SAC’04) March 2004, Nicosia, Cyprus

Application of map images

Server side Operations: Rasterization Compression Benefits: Independent on vector formats Large map databases at server side Low cost client side applications

Client side = + Operations: Decompression Viewing

Map image compression

Text rasterization Hershey vector font (0,0)+(5,10)+(8,0)+(–1, –1) + (2,5)+ (6,5) =

Text rotation Text is stored as bitmaps: Same text after rotation consists from different bitmaps

Text rotation process

Text control data

MISS file structure

Text layer

Decoding Generic region decoding Text region decoding 1.Decoding of symbols bitmaps 2.Decoding of control data

Experimental results

Statistical data of the text rasterization Size of dictionary Number of symbols Size of compressed blocks Strip data X sizes Y sizes Strip lengths  X coordinates  Y coordinates Bitmap’s indexes

Conclusions Improved map image compression... but where was the intelligence, computational logic, or image analysis? Intelligence was that we avoided all AI and IA operations at the client side.