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In image processing, computer vision and related fields, an image moment is a certain particular weighted average (moment) of the image pixels' intensities, or a function of such moments, usually chosen to have some attractive property or interpretation. Image moments are useful to describe objects after segmentation. Simple properties of the image which are found ''via'' image moments include area (or total intensity), its centroid, and information about its orientation. == Raw moments == For a 2D continuous function ''f''(''x'',''y'') the moment (sometimes called "raw moment") of order (''p'' + ''q'') is defined as : for ''p'',''q'' = 0,1,2,... Adapting this to scalar (greyscale) image with pixel intensities ''I''(''x'',''y''), raw image moments ''Mij'' are calculated by : In some cases, this may be calculated by considering the image as a probability density function, ''i.e.'', by dividing the above by : A uniqueness theorem (Hu ()) states that if ''f''(''x'',''y'') is piecewise continuous and has nonzero values only in a finite part of the ''xy'' plane, moments of all orders exist, and the moment sequence (''Mpq'') is uniquely determined by ''f''(''x'',''y''). Conversely, (''Mpq'') uniquely determines ''f''(''x'',''y''). In practice, the image is summarized with functions of a few lower order moments. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「image moment」の詳細全文を読む スポンサード リンク
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