ough ▁space . ▁The ▁intersection ▁of ▁these ▁sin us oid al ▁surfaces ▁indicates ▁presence ▁of ▁a ▁plane . ▁A ▁more ▁general ▁approach ▁for ▁more ▁than ▁ 3 ▁dimensions ▁requires ▁search ▁he ur istics ▁to ▁remain ▁feas ible . ▁ ▁H ough ▁transform ▁has ▁also ▁been ▁used ▁to ▁find ▁cyl ind rical ▁objects ▁in ▁point ▁clouds ▁using ▁a ▁two ▁step ▁approach . ▁The ▁first ▁step ▁finds ▁the ▁orientation ▁of ▁the ▁cyl inder ▁and ▁the ▁second ▁step ▁finds ▁the ▁position ▁and ▁radius . ▁ ▁Using ▁weight ed ▁features ▁One ▁common ▁variation ▁ ▁detail . ▁ ▁That ▁is , ▁finding ▁the ▁b ins ▁with ▁the ▁highest ▁count ▁in ▁one ▁stage ▁can ▁be ▁used ▁to ▁const rain ▁the ▁range ▁of ▁values ▁searched ▁in ▁the ▁next . ▁ ▁Care fully ▁chosen ▁parameter ▁space ▁ ▁A ▁high - dimensional ▁parameter ▁space ▁for ▁the ▁H ough ▁transform ▁is ▁not ▁only ▁slow , ▁but ▁if ▁implemented ▁without ▁for eth ought ▁can ▁easily ▁over run ▁the ▁available ▁memory . ▁ ▁Even ▁if ▁the ▁programming ▁environment ▁allows ▁the ▁allocation ▁of ▁an ▁array ▁larger ▁than ▁the ▁available ▁memory ▁space ▁through ▁virtual ▁memory , ▁the ▁number ▁of ▁page ▁sw aps ▁required ▁for ▁this ▁will ▁be ▁very ▁demand ing ▁because ▁the ▁accum ulator ▁array ▁is ▁used ▁in ▁a ▁randomly ▁accessed ▁fashion , ▁rarely ▁stopping ▁in ▁cont igu ous ▁memory ▁as ▁it ▁ski ps ▁from ▁index ▁to ▁index . ▁ ▁Consider ▁the ▁task ▁of ▁finding ▁elli ps es ▁in ▁an ▁ 8 0 0 x 6 0 0 ▁image . ▁Assuming ▁that ▁the ▁rad ii ▁of ▁the