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bestpractices:welcome [2019/05/16 17:55]
pdufour [Image dataset]
bestpractices:welcome [2019/05/20 18:24] (current)
pdufour
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-====== Best Practices ======+ ====== Best Practices ======
 Create a coherente dataset Create a coherente dataset
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 Inspire you Inspire you
 ===== Image dataset ===== ===== Image dataset =====
-First step to have the better experience is to compose a coherent dataset. To create the database, Let'​s ​use explain how work our Image recognition.+First step to have the better experience is to compose a coherent dataset. To create the database, Let'​s ​us explain how work our Image recognition. 
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 +The visual search solutions allow to find, from a query image, identical or similar visuals in images databases. The search is based on object recognition,​ shape or color and depends on upon the content of an image, rather than on textual information.  
 ==== Images transformation robustess ==== ==== Images transformation robustess ====
  
 LTU Engine’s image matching technology is robust against several types of image transformations,​ detecting not only the exact same image, but also modified versions of the original image and object matches (photographs of same object). LTU Engine’s image matching technology is robust against several types of image transformations,​ detecting not only the exact same image, but also modified versions of the original image and object matches (photographs of same object).
  
-This part illustrates the types of image transformations that LTU Engine can handle in order to identify a match. ​Image transformations can be broadly divided into several groups:+Image transformations can be broadly divided into several groups:
   * __**Geometric transformations:​**__ Includes scale changes, rotations, translations,​ flips and projective transformations.   * __**Geometric transformations:​**__ Includes scale changes, rotations, translations,​ flips and projective transformations.
   * __**Photometric transformations:​**__ Includes color space conversions,​ gray level transformations,​ changes in hue, brightness and contrast.   * __**Photometric transformations:​**__ Includes color space conversions,​ gray level transformations,​ changes in hue, brightness and contrast.
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 Often images may be modified with a combination of the above transformations. However, the LTU image matching technology is robust even in those instances. The matching technology easily matched the above combination which includes Gray scale, blur, re-encoding,​ projective transformation and overlay composite transformations. ​ Often images may be modified with a combination of the above transformations. However, the LTU image matching technology is robust even in those instances. The matching technology easily matched the above combination which includes Gray scale, blur, re-encoding,​ projective transformation and overlay composite transformations. ​
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 +For more information,​ consult the white paper.
 +==== Limitation ====
 +==== Images quality ====
 +
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 ===== Enrichissement ===== ===== Enrichissement =====