Abstract
A measurement of leaf area is apparently simple and fundamental. Various methods are available to measure leaf area. Available methods are time consuming, humdrum and laborious. Less expensive methods involving image processing based on video camera images and computer programs for analysis of these images have been alternative for all other techniques for leaf area assessment. In this paper we introduce a computer program that can calculate leaf area meter based on the pixel count in very short time and highly accurate by image processing. This program provides very fast, inexpensive and highly accurate measurement.
Highlights
Measuring the leaf area of plants is an interest of many scientific disciplines
Less expensive methods involving image processing based on video camera images and computer programs for analysis of these images have been alternative for all other techniques for leaf area assessment. (Hargrove & Crossley, 1988; 14 Hagerup et al, 1990)
Image processing is promising to overcome these problems but there is still long way for automatic interpretation of plant images. (Yu Song,) estimating plant characteristics such as leaf area stem length or fruit size and color challenging with image analysis, image analysis could contribute greatly to increased quality and yield of plant product due to its cheaper and practical usage
Summary
Determining the distribution and changes of leaf area is significant for assessing growth, physiology analysis and strength of vegetation on the planet. It is very important as a parameter in land-surface processes and climate models. General strategy of measuring the leaf areas is one-side surface area measurement of all individuals’ leaves This is accepted as a powerful strategy to diagnose plant productivity. Less expensive methods involving image processing based on video camera images and computer programs for analysis of these images have been alternative for all other techniques for leaf area assessment. Image processing is promising to overcome these problems but there is still long way for automatic interpretation of plant images. (Yu Song,) estimating plant characteristics such as leaf area stem length or fruit size and color challenging with image analysis, image analysis could contribute greatly to increased quality and yield of plant product due to its cheaper and practical usage
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