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General Purpose Vision Tools
 
AISYS OvkTexture module
AISYS OvkTexture module 產品特點
  • OvkTexture is based on AISYS generial purpose vision tools and provides fast analysis and classification for texture
  • Multiple Development Platforms:OvkTexture provide excellent support for WINDOWS and supported development platforms include : Visual Basic、Visual C++、Visual C#、C++ Builder、Delphi
  • Good compatibility in hardware : fully support AISYS all seriels image capture device includes a video capture card and camera industries
  • Good compatibility in software : fully support AISYS all seriels software utility and barebone system product
簡介
  • Provides fast analysis and classification for texture
  • High computing performance, fully support 32/64bit platform of windows
  • Omnidirectional analysis, regardless of the direction of texture elements, OvkTexture always exibits powerful analysis capability
  • No prior learning for texture analysis and classification
  • Incorperating with OvkBlob can separate different texture easily
  • AISYS FAE team provides the best consultant and service which dramatically reduce development cost
  • Excellent C/P ratio


Figure I: Texture on PCB trace, the original image to be processed (ROI size 500x500)
Stpe 1->2->3, it costs 48.08ms of analysis time (Intel Core i7-3610QM with 2GB RAM)

 
Figure 2: Textures of printed matter, the original image to be processed (ROI size 500x500)
Stpe 1->2->3, it costs 47.79ms of analysis time (Intel Core i7-3610QM with 2GB RAM)


Figure 3: Leather texture on cotton material, the original image to be processed (ROI size 500x500)
Stpe 1->2->3, it costs 60.86ms of analysis time (Intel Core i7-3610QM with 2GB RAM)


Figure 4: Texture on cloth, the original image to be processed (ROI size 500x500)
Stpe 1->2->3, it costs 29.67ms of analysis time (Intel Core i7-3610QM with 2GB RAM)


Figure 3: Leather texture on stone, the original image to be processed (ROI size 500x500)
Stpe 1->2->3, it costs 38.56ms of analysis time (Intel Core i7-3610QM with 2GB RAM)

 

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