fixing all RGB instances to BGR where needed

doc/py_tutorials/py_imgproc/py_colorspaces/py_colorspaces.markdown

@@ -34,7 +34,7 @@ Object Tracking
 ---------------
 
 Now we know how to convert BGR image to HSV, we can use this to extract a colored object. In HSV, it
-is more easier to represent a color than RGB color-space. In our application, we will try to extract
+is more easier to represent a color than in BGR color-space. In our application, we will try to extract
 a blue colored object. So here is the method:
 
 -   Take each frame of the video

doc/py_tutorials/py_video/py_lucas_kanade/py_lucas_kanade.markdown

@@ -194,15 +194,15 @@ while(1):
     mag, ang = cv2.cartToPolar(flow[...,0], flow[...,1])
     hsv[...,0] = ang*180/np.pi/2
     hsv[...,2] = cv2.normalize(mag,None,0,255,cv2.NORM_MINMAX)
-    rgb = cv2.cvtColor(hsv,cv2.COLOR_HSV2BGR)
+    bgr = cv2.cvtColor(hsv,cv2.COLOR_HSV2BGR)
 
-    cv2.imshow('frame2',rgb)
+    cv2.imshow('frame2',bgr)
     k = cv2.waitKey(30) & 0xff
     if k == 27:
         break
     elif k == ord('s'):
         cv2.imwrite('opticalfb.png',frame2)
-        cv2.imwrite('opticalhsv.png',rgb)
+        cv2.imwrite('opticalhsv.png',bgr)
     prvs = next
 
 cap.release()