TY - JOUR

T1 - Counting touching wheat grains in images based on elliptical approximation

AU - Avzalov, D. R.

AU - Komyshev, E. G.

AU - Afonnikov, D. A.

N1 - Avzalov D.R., Komyshev E.G., Afonnikov D.A. Counting touching wheat grains in images based on elliptical approximation. Vavi lov skii Zhurnal Genetiki i Selektsii = Vavilov J Genet Breed. 2025;29(4):608-614. doi 10.18699/vjgb-25-64. The work was funded by the Kurchatov Genomic Center of ICG SB RAS, Agreement No. 075-15-2019-1662 with the Ministry of Science and Higher Education of the Russian Federation.

PY - 2025

Y1 - 2025

N2 - The number of grains of a cereal plant characterizes its yield, while grain size and shape are closely related to its weight. To estimate the number of grains, their shape and size, digital image analysis is now generally used. The grains in such images may be completely separated, touching or densely packed. In the first case, the simplest binarization/segmentation algorithms, such as the watershed algorithm, can achieve high accuracy in segmentation and counting grains in an image. However, in the case of touching grains, simple machine vision algorithms may lead to inaccuracies in determining the contours of individual grains. Therefore, methods for accurately determining the contours of individual grains when they are in contact are relevant. One approach is based on the search for pixels of the grain contact area, in particular, by identification of concave points on the grain contour boundary. However, some grains may have chips, depressions and bulges, which leads to the identification of the corner points that do not correspond to the grain contact region. Additional data processing is required to avoid these errors. In this paper, we propose an algorithm for the identification of wheat grains in an image and determine their boundaries in the case when they are touching. The algorithm is based on using a modification of the concave point search algorithm and utilizes a method of assigning contour boundary pixels to a single grain based on approximation of grain contours by ellipses. We have shown that the proposed algorithm can identify grains in the image more accurately compared to the algorithm without such approximation and the watershed algorithm. However, the time cost for such an algorithm is significant and grows rapidly with increasing number of grains and contours including multiple grains.

AB - The number of grains of a cereal plant characterizes its yield, while grain size and shape are closely related to its weight. To estimate the number of grains, their shape and size, digital image analysis is now generally used. The grains in such images may be completely separated, touching or densely packed. In the first case, the simplest binarization/segmentation algorithms, such as the watershed algorithm, can achieve high accuracy in segmentation and counting grains in an image. However, in the case of touching grains, simple machine vision algorithms may lead to inaccuracies in determining the contours of individual grains. Therefore, methods for accurately determining the contours of individual grains when they are in contact are relevant. One approach is based on the search for pixels of the grain contact area, in particular, by identification of concave points on the grain contour boundary. However, some grains may have chips, depressions and bulges, which leads to the identification of the corner points that do not correspond to the grain contact region. Additional data processing is required to avoid these errors. In this paper, we propose an algorithm for the identification of wheat grains in an image and determine their boundaries in the case when they are touching. The algorithm is based on using a modification of the concave point search algorithm and utilizes a method of assigning contour boundary pixels to a single grain based on approximation of grain contours by ellipses. We have shown that the proposed algorithm can identify grains in the image more accurately compared to the algorithm without such approximation and the watershed algorithm. However, the time cost for such an algorithm is significant and grows rapidly with increasing number of grains and contours including multiple grains.

UR - https://www.scopus.com/pages/publications/105013089655

UR - https://www.mendeley.com/catalogue/f70725dc-71fc-3e36-ad76-9d0e8a54609d/

U2 - 10.18699/vjgb-25-64

DO - 10.18699/vjgb-25-64

M3 - Article

C2 - 40697937

VL - 29

SP - 608

EP - 614

JO - Вавиловский журнал генетики и селекции

JF - Вавиловский журнал генетики и селекции

SN - 2500-0462

IS - 4

M1 - 13

ER -