Modeling of the high-performance PLD-based sectioning method for classification of the shape of optical object images

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Table 1 Classification of surface types by coefficient r

Shape of the longitudinal section	Factor values			Inaccuracy δr_v
Shape of the longitudinal section	r _s	${\tilde{r}}_{v}$	r _v	Inaccuracy δr_v
1. Prism, cylinder	1	11/12 ≈ 0.92	1	1/12 ≈ 0.083
2. Pyramid, cone	1/4 = 0.25	2/3 ≈ 0.67	2/3 ≈ 0.67	0
3. Hemisphere	7/12 ≈ 0.58	7/9 ≈ 0.78	7/9 ≈ 0.78	0
4. Hemisphere with a base	3/4 = 0.75	5/6 ≈ 0.83	5/6 ≈ 0.83	0
5. Gaussoid	ln(4/3)/ln2 ≈ 0.415	8.66/12 ≈ 0.722	1/2 ln ≈ 0.721	≈ 0
$(1 / \sqrt{2 π}) exp \{- (x^{2} + y^{2}) / 2\}$	ln(4/3)/ln2 ≈ 0.415	8.66/12 ≈ 0.722	1/2 ln ≈ 0.721	≈ 0