رنگ هسٽونامو
Wikipedia طرفان
ڳڻپيوڪر چٽيات ۾، رنگ هسٽونامو هڪ نمائندگي آهي of an image derived by counting the هر عڪسل جو 'رنگ'. اهو خيال مائيڪل سوين ۽ ڊانا بالرڊ 1991ع ۾ پيش ڪيو ۽ آهي خاص طور اتي استعمال ٿيندو آهي جتي الخوارضميءَ جي چونڊ ۾ پراسيسڪاريءَ جي رفتار هڪ خاص فيڪٽر هجي.
, or where a specific object, rather than a more abstract class of objects is required to be identified; as noted by Swain and Ballard, "It may not be helpful to model coffee cups as being red and white, but yours may be."
رنگ هسٽوناما لچڪدار ڪنسٽرڪٽ آهن، جيڪي متفرق رنگ پولار، جهڙوڪ ڳسن، ڳس-ڪروميٽيسٽي يا ڪو ٻيو رنگ پولار رکندڙ عڪسن لاءِ جوڙي سگھجن ٿا.
ڪنهن عڪس جو هسٽونامو جوڙڻ لاءِ عڪس اندر هر رنگي عدد رکندڙ عڪسلون ڳڻبيون آهن.
red | |||||
0-63 | 64-127 | 128-191 | 192-255 | ||
blue | 0-63 | 43 | 78 | 18 | 0 |
64-127 | 45 | 67 | 33 | 2 | |
128-191 | 127 | 58 | 25 | 8 | |
192-255 | 140 | 47 | 47 | 13 |
This provides a far more compact overview of the data in an image than knowing the exact value of every pixel. The color histogram of an image is invariant with translation and rotation about the viewing axis, and varies only slowly with the angle of view. This makes the color histogram particularly suited to recognising an object of unknown position and rotation within a scene. Importantly, translation of an RGB image into the illumination invariant rg-chromaticity space allows the histogram to operate well in varying light levels.
The main drawback of histograms is that the representation is solely dependent of the color of the object being studied. There is no way to distinguish a red and white cup from a red and white plate. Put another way, histogram-based algorithms have no concept of a generic 'cup', and a model of our red and white cup is no use when given an otherwise identical blue and white cup.
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- Histogram equalization