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Algorithm for an Automated Clarias gariepinus Fecundity Estimation Technique Using Spline Interpolation and Gaussian Quadrature

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@article{IJASEIT10188,
   author = {Abdul Aziz K Abdul Hamid and Norfazlina Amirudin and Masduki Mohammad Morni and Sumazly Sulaiman},
   title = {Algorithm for an Automated Clarias gariepinus Fecundity Estimation Technique Using Spline Interpolation and Gaussian Quadrature},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {10},
   number = {4},
   year = {2020},
   pages = {1465--1470},
   keywords = {fecundity; eye detection; image processing; mathematical theories; ground truth.},
   abstract = {Fecundity is essential in the field of population ecology, where the number of eggs is measured to get the actual reproductive rate of an organism. The estimation of fecundity is essential for an accurate study of biology and population dynamics of fish species. This estimation can be developed using the gravimetric method (weight method) to calculate the number of eggs. However, this method still requires experienced technicians and much time and effort to compute the number of eggs manually. The increasing growth in both hardware and software have led to many improvements in imaging technology. Hence, this research addresses the problem of employing constructing a computer vision algorithm. This paper introduced the automatic fecundity estimation method, which applied simple mathematic theories and image processing algorithm to estimate the fecundity of African catfish (Clarias gariepinus). From the image of the fish, the fish’s eye was be detected using a modified Haar Cascade Classifier Algorithm and appointed axis line where the eye becomes the origin point. Next, we identify the region of interest, which reflects the fish's fecundity to obtain the pixels corresponding to the silhouette of the region as coordinates in Euclidean space, which are then represented with a function using cubic interpolation function. Using this function, we compute the region of interest using an integral numerical approach, e.g., Gaussian Quadrature. From the result, we compared with the ground truth to get the estimation of the number of eggs.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10188},
   doi = {10.18517/ijaseit.10.4.10188}
}

EndNote

%A Abdul Hamid, Abdul Aziz K
%A Amirudin, Norfazlina
%A Mohammad Morni, Masduki
%A Sulaiman, Sumazly
%D 2020
%T Algorithm for an Automated Clarias gariepinus Fecundity Estimation Technique Using Spline Interpolation and Gaussian Quadrature
%B 2020
%9 fecundity; eye detection; image processing; mathematical theories; ground truth.
%! Algorithm for an Automated Clarias gariepinus Fecundity Estimation Technique Using Spline Interpolation and Gaussian Quadrature
%K fecundity; eye detection; image processing; mathematical theories; ground truth.
%X Fecundity is essential in the field of population ecology, where the number of eggs is measured to get the actual reproductive rate of an organism. The estimation of fecundity is essential for an accurate study of biology and population dynamics of fish species. This estimation can be developed using the gravimetric method (weight method) to calculate the number of eggs. However, this method still requires experienced technicians and much time and effort to compute the number of eggs manually. The increasing growth in both hardware and software have led to many improvements in imaging technology. Hence, this research addresses the problem of employing constructing a computer vision algorithm. This paper introduced the automatic fecundity estimation method, which applied simple mathematic theories and image processing algorithm to estimate the fecundity of African catfish (Clarias gariepinus). From the image of the fish, the fish’s eye was be detected using a modified Haar Cascade Classifier Algorithm and appointed axis line where the eye becomes the origin point. Next, we identify the region of interest, which reflects the fish's fecundity to obtain the pixels corresponding to the silhouette of the region as coordinates in Euclidean space, which are then represented with a function using cubic interpolation function. Using this function, we compute the region of interest using an integral numerical approach, e.g., Gaussian Quadrature. From the result, we compared with the ground truth to get the estimation of the number of eggs.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10188
%R doi:10.18517/ijaseit.10.4.10188
%J International Journal on Advanced Science, Engineering and Information Technology
%V 10
%N 4
%@ 2088-5334

IEEE

Abdul Aziz K Abdul Hamid,Norfazlina Amirudin,Masduki Mohammad Morni and Sumazly Sulaiman,"Algorithm for an Automated Clarias gariepinus Fecundity Estimation Technique Using Spline Interpolation and Gaussian Quadrature," International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 4, pp. 1465-1470, 2020. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.10.4.10188.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Abdul Hamid, Abdul Aziz K
AU  - Amirudin, Norfazlina
AU  - Mohammad Morni, Masduki
AU  - Sulaiman, Sumazly
PY  - 2020
TI  - Algorithm for an Automated Clarias gariepinus Fecundity Estimation Technique Using Spline Interpolation and Gaussian Quadrature
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 10 (2020) No. 4
Y2  - 2020
SP  - 1465
EP  - 1470
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - fecundity; eye detection; image processing; mathematical theories; ground truth.
N2  - Fecundity is essential in the field of population ecology, where the number of eggs is measured to get the actual reproductive rate of an organism. The estimation of fecundity is essential for an accurate study of biology and population dynamics of fish species. This estimation can be developed using the gravimetric method (weight method) to calculate the number of eggs. However, this method still requires experienced technicians and much time and effort to compute the number of eggs manually. The increasing growth in both hardware and software have led to many improvements in imaging technology. Hence, this research addresses the problem of employing constructing a computer vision algorithm. This paper introduced the automatic fecundity estimation method, which applied simple mathematic theories and image processing algorithm to estimate the fecundity of African catfish (Clarias gariepinus). From the image of the fish, the fish’s eye was be detected using a modified Haar Cascade Classifier Algorithm and appointed axis line where the eye becomes the origin point. Next, we identify the region of interest, which reflects the fish's fecundity to obtain the pixels corresponding to the silhouette of the region as coordinates in Euclidean space, which are then represented with a function using cubic interpolation function. Using this function, we compute the region of interest using an integral numerical approach, e.g., Gaussian Quadrature. From the result, we compared with the ground truth to get the estimation of the number of eggs.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10188
DO  - 10.18517/ijaseit.10.4.10188

RefWorks

RT Journal Article
ID 10188
A1 Abdul Hamid, Abdul Aziz K
A1 Amirudin, Norfazlina
A1 Mohammad Morni, Masduki
A1 Sulaiman, Sumazly
T1 Algorithm for an Automated Clarias gariepinus Fecundity Estimation Technique Using Spline Interpolation and Gaussian Quadrature
JF International Journal on Advanced Science, Engineering and Information Technology
VO 10
IS 4
YR 2020
SP 1465
OP 1470
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 fecundity; eye detection; image processing; mathematical theories; ground truth.
AB Fecundity is essential in the field of population ecology, where the number of eggs is measured to get the actual reproductive rate of an organism. The estimation of fecundity is essential for an accurate study of biology and population dynamics of fish species. This estimation can be developed using the gravimetric method (weight method) to calculate the number of eggs. However, this method still requires experienced technicians and much time and effort to compute the number of eggs manually. The increasing growth in both hardware and software have led to many improvements in imaging technology. Hence, this research addresses the problem of employing constructing a computer vision algorithm. This paper introduced the automatic fecundity estimation method, which applied simple mathematic theories and image processing algorithm to estimate the fecundity of African catfish (Clarias gariepinus). From the image of the fish, the fish’s eye was be detected using a modified Haar Cascade Classifier Algorithm and appointed axis line where the eye becomes the origin point. Next, we identify the region of interest, which reflects the fish's fecundity to obtain the pixels corresponding to the silhouette of the region as coordinates in Euclidean space, which are then represented with a function using cubic interpolation function. Using this function, we compute the region of interest using an integral numerical approach, e.g., Gaussian Quadrature. From the result, we compared with the ground truth to get the estimation of the number of eggs.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=10188
DO  - 10.18517/ijaseit.10.4.10188