Comparison of automatic and interactive thresholding of hemispherical photography

A. Inoue, K. Yamamoto and N. Mizoue
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A. Inoue: Laboratory of Forest Ecology, Faculty of Environmental and Symbiotic Sciences, Prefectural University of Kumamoto, Kumamoto, Japan
K. Yamamoto: Laboratory of Forest Environment and Resources, Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, Japan
N. Mizoue: Laboratory of Forest Planning, Faculty of Agriculture, Kyushu University, Fukuoka, Japan

Journal of Forest Science, 2011, vol. 57, issue 2, 78-87

Abstract: This study presents the effects of operator bias and variation in interactive thresholding on the estimation of light environment using hemispherical photography. Twenty-one hemispherical photographs taken beneath a wide range of canopy densities were visually converted to binary images twice by 21 operators, and then the gap fraction was computed from the images. The interactive threshold varied greatly among the different operators and within a single operator, which resulted in a considerable operator bias and variation in the gap fraction. This study also compared three widely used automatic thresholding algorithms, which were installed in freely available software LIA for Win32 for analyzing hemispherical photography, with interactive thresholding using the same photographs. The median of the interactive threshold by repetitive interactive thresholdings from 21 operators was assumed to be correct for the comparison. The results indicated that MINIMUM was considered to be a better algorithm than the other ones installed in LIA32 when the gap fraction was over 10%. However, VARIANCE seemed to be superior to MINIMUM under the low gap fraction and the cloudy sky condition with dark and white clouds. This implied that MINIMUM or VARIANCE should be used for analyzing hemispherical photographs with LIA32. In conclusion, we need to pay attention to the selection of the automatic thresholding algorithm and the sky condition when taking hemispherical photographs.

Keywords: image analysis; LIA for Win32; light environment; operator bias; operator variation (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnljfs:v:57:y:2011:i:2:id:68-2010-jfs

DOI: 10.17221/68/2010-JFS

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