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Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering
International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825.
1
Geometric properties of Kohanz apple fruits
Mohammad Bagher Lak
(Young Researchers Club, Science and Research Branch, Islamic Azad University, Tehran, Iran)
Abstract: Kohanz is a domestic apple variety which is grown in Iran. It is sensitive to packing
conditions. Bad packages normally cause decline in its quality. Therefore, apple’s geometric
properties are of important consideration in the design of the fruit’s packaging facilities. In this
study, a sample of 38 freshly harvested apple fruits was obtained, 82 images of their sides were
acquired and geometric dimensions were measured. Their axial dimensions, equivalent diameter
and sphericity were obtained using a vernier caliper with accuracy of 0.05 mm, while the cross
section area, eccentricity, perimeter and roundness were measured using a color based image
processing method. Their arithmetic mean diameter was 57.6 mm, while the mean eccentricity
was 0.3058, mean roundness was 0.5858 and mean sphericity was 0.9985. Therefore, the
packing design must be collections of spheroid spaces with diameters of about 6.8 mm which will
include all of the apples.
Keywords: eccentricity, equivalent diameter, image processing, roundness, sphericity
1. Introduction
Among all the fruits produced in Iran, apple is the most important economical and industrial fruit
(Meisami-asl et al, 2009). Kohanz apple is one of the famous Iranian domestic apple varieties.
The fruits are currently filled in woody or plastic made boxes without any arrangement. The
packages usually include some damaged fruits.
Bruise damage is a major cause of fruit quality loss (Zarifneshat et al., 2010). The packing
method causes compression damage in which fruit are bruised as they are pushed into a bin or
bag (Kupferman, 2006). Conformity of size is particularly desirable for packaging and display
purposes (Studman, 2001). Therefore, apples should be sorted into categories in order to provide
better markets. The sorting method can be size-based in which they are classified according to
their geometric properties.
Aviara et al. (2007), Hasankhani (2008), Amiriparian et al. (2008), Meisami-asl et al. (2009), and
Zarifneshat et al. (2010) worked on estimation of some agricultural products physical properties.
Application of image processing based methods in agricultural activities has been developed for
years. The applications involve activities such as auto-guidance (Benson et al., 2003; Han et al.,
2004), weed control (Nieuwenhuizen et al., 2007; Ghazali et al., 2009), harvesting (Lak et al.,
2010; Bulanon and Kataoka, 2010), yield monitoring (Chinchuluun et al., 2007; Annamalai, 2004)
and post harvest (Amiriparian et al., 2008; Rao and Renganathan, 2002; Zion et al., 1999).
Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering
International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825.
2
Geometric properties of fruits can be investigated by machine vision based methods (Rao and
Renganathan, 2002; Rashidi and Seyfi, 2007). Aviara et al. (2007) determined physical
properties of guna fruits; Davies (2010) investigated the physical properties of arigo seeds; and
Hasankhani (2008) studied some geometric properties (area, volume, shape, external defects such
as: greening, cracks and insect attack defects) of potato using machine vision. Amiriparian et al.
(2008) estimated three agricultural products’ (apple (Golden Delicious), pistachio and onion)
volume using image processing.
It is likely that consumer demand for improved quality, longer storage life and guaranteed
product safety will continue to grow (Studman, 2001). Therefore, providing an appropriate
package will promote Kohanz apple marketing.
The main objective of this study is to determine the freshly harvested Kohanz apple’s geometric
properties. The axial dimensions, namely, length L (maximum dimension), thickness T (medium
dimension) and width W (minimum dimension) were measured manually, meanwhile, cross
sectional areas (pixels included in detected feature), perimeters (pixels surrounding detected
feature), eccentricities (the ratio of the distance between the foci of the ellipse and its major axis
length ( 10   and  circle = 0) (Gonzalez, et al., 2004), equivalent diameters (the diameter of a
circle with the same area as the region (Gonzalez, et al., 2004), and roundness of sides of the
fruits are the properties which can be defined using image processing. Sphericity was calculated
using manually measured quantities.
Good packaging would vouch for better marketing. While, identification of fruits’ geometric
properties is required to design appropriate package size. Therefore, the main goal of this study
is to define the optimum spheroid packing size for Kohanz apples using its geometric properties.
2. Materials and Methods
Geometric properties of Kohanz apples were divided into two categories: parameters which could
be measured using a vernier caliper; and properties that can be extracted from processed images.
2.1 Manual measured parameters
A sample of 38 apples was selected randomly from a grove in Hamedan, western Iran. The axial
dimensions, namely, length L, thickness T, and width W were measured using a vernier caliper
(TAKA
Vernier Caliper, 200×0.05mm). Arithmetic mean diameter Da, and sphericity  were
calculated using Equation (1) and (2) as follows (Kibar and Öztürk, 2008; Jain and Bal, 1997).
3
WTL
Da


(1)
Where:
D a= arithmetic mean diameter (mm), W = width (mm), T = thickness (mm), and L = length (mm)
Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering
International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825.
3
3 2
)2(
L
WTLWT 

(2)
Where:
 = sphericity (dimensionless)
2.2 Image processing extracted properties
A digital camera (Sony, DSC-H5, Color CCD Camera) was used to acquire 82 images of 38
apples’ sides. At least, two sides of each apple were imaged. Format of the images was jpeg and
they were in RGB (red-green-blue) color space. Because some of the samples were not
symmetric, they were imaged from more than two sides.
The images were converted to L*a*b color space. The L*a*b* space consists of a luminosity
layer L*, chromaticity layer a* indicating where color falls along the red-green axis, and
chromaticity layer b* indicating where the color falls along the blue-yellow axis (Matlab, 2007).
Then, they were converted to binary form, noise-reduced, labeled, and the properties were
extracted. The properties were: area, eccentricity and perimeter. Area and perimeter were in
terms of pixel and eccentricity was dimensionless.
Roundness was estimated using the relationship between area and perimeter (Equation (3)) and it
was also dimensionless.
2
4
P
A
R

 (MATLAB, 2007)
(3)
Where:
R = roundness (dimensionless), A = area (pixel), and P = perimeter (pixel).
3. Results and Discussion
Apples’ length, thickness and width were measured; therefore their equivalent diameter and
sphericity were calculated by the data. Table 1 shows the descriptive statistics of properties
which were measured by means of a caliper.
All the apples were imaged at least with two sides (Figure 1). First, the images were converted to
L*a*b color space (Figure 2), then they were converted to binary form (Figure 3). Finally, they
were noise-reduced and some properties were extracted (Figure 4). Area, eccentricity and
perimeter were the properties extracted from processed images. The roundness was calculated by
Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering
International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825.
4
using a function between area and perimeter (Equation (3)). The descriptive statistics of apples’
properties which obtained from image processing are listed in Table 2.
a b
Figure 1 Typical original images acquired from two sides of apples
a b
Figure 2 Images in L*a*b color space
Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering
International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825.
5
a b
Figure 3 Binary images
a b
Figure 4 Noise-reduced binary images
Table 1 Descriptive statistics of manually measured properties of apples
Properties Na
Range Minimum Maximum Mean Std. Deviation Variance
Lb
82 17.45 49.65 67.10 60.05 3.0189 9.114
Tc
82 15.50 49.50 65.00 57.99 2.9438 8.666
Wd
82 13.50 47.00 60.50 54.83 3.1641 10.011
Da
e
82 15.48 48.72 64.20 57.62 1.7572 3.088
a
Sample size
b
Length in millimeter
c
Thickness in millimeter
d
Width in millimeter
e
Arithmetic mean diameter in millimeter
Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering
International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825.
6
Table 2 Descriptive statistics of the properties measured by image processing
N Range Minimum Maximum Mean Std.
Deviation
Variance
Area (pixels) 82 1014172 1044468 2058640 1494828.10 204750.905 4.192E10
Eccentricity (pixels) 82 0.6758 0.0446 0.7204 0.3058 0.1116 0.012
Equivalent Diameter (pixels) 82 15.03 48.72 63.75 57.63 2.8285 8.000
Perimeter (pixels) 82 13130.5 4080.5 17211.0 6321.7 2239.0 5013152.3
Roundness (dimensionless) 82 0.7881 0.0526 0.8407 0.5858 0.2396 0.057
Sphericity (dimensionless) 82 0.0051 0.9948 0.9999 0.9985 0.0012 0.000
Mean and range of length, thickness, width, eccentricity, equivalent diameter, roundness and
sphericity were 60.05[49.65 67.10], 57.99[49.50 65.00], 54.83[47.00 60.50], 0.3058
[0.0446 0.7204], 57.63[48.72 63.75], 0.5858  [0.0526 0.8407], and 0.9985  [0.9948 0.9999]
respectively (Table 1 and Table 2).
Extracted geometric properties of Kohanz apples were of at least two sides of each apple,
therefore, the properties involve three dimension properties of them. The maximum, mean and
minimum diameters of Golab apple were 65.04, 53.50 and 35.14 mm respectively (Meisami-asl,
2009); meanwhile the measures were 64.20, 57.62, and 48.72 mm for Kohanz variety.
The apples’ sphericity ranges show that the apples can be considered as spheres with diameters
equal to equivalent diameters. On the other hand, their maximum dimension is their length.
Therefore, their packing design must be collections of spheroid spaces with diameters of about 68
mm which includes all of them.
4. Conclusions
This paper considered Kohanz apple’s geometric properties. Their length, thickness and width
were measured by caliper. Their equivalent diameters and sphericity were calculated. Their area,
perimeter and eccentricity were extracted by image processing and roundness was computed by a
function with area and perimeter.
Finally it was determined that a collection of spheroid spaces with diameters of about 68 mm will
be the most appropriate package design.
References
Amiriparian, J., M. H. Khoshtaghaza, and E. Kabir. 2008. A practical model for estimation of
agricultural products volume using machine vision (in Persian). In Proc. 5th National
Congress on Agricultural Machinery Engineering and Mechanization, Ferdowsi University of
Mashhad, Iran.
Annamalai, P. 2004. Citrus yield mapping system using machine vision. M.S. Thesis,
Department of Agricultural and Biological Engineering, University of Florida. 81.
Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering
International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825.
7
Aviara, N. A, S. K. Shittu, and M. A. Haque. 2007. Physical properties of guna fruits relevant in
bulk handling and mechanical processing. International Agrophysics, 21(1): 7-16.
Benson, E. R., J. F. Reid, and Q. Zhang. 2003. Machine vision-based guidance system for
agricultural grain harvester using cut-edge detection. Biosystems Engineering, 86 (4), 389–
398.
Bulanon, D. M., and T. Kataoka . 2010. Fruit detection system and an end effector for robotic
harvesting of Fuji apples. CIGR Journal, 12(1): 203-210.
Chinchuluun, R., W. S. Lee, and R. Ehsani. 2007. Citrus yield mapping system on a canopy,
shake and catch harvester. In Proc. ASABE Annual International Meeting, Paper Number:
073050.
Davies, R. M. 2010. Some physical properties of arigo seeds. International Agrophysics, 24(1):
89-92.
Ghazali, K. H, M. M. Mustafa, and A. Hussain. 2009. Machine vision system for automatic
weeding strategy in oil palm plantation using image filtering technique. International Journal
of Electrical, Computer, and Systems Engineering 3:4, 193-197.
Gonzalez, R. C., R. E. Woods, and S. L. Eddins. 2004. Digital image processing using
MATLAB. Pearson Education. 609 p.
Han, S., Q. Zhang, B. Ni, and J. F. Reid. 2004. A guidance directrix approach to vision-based
vehicle guidance systems. Computers and Electronics in Agriculture, 43: 179-195.
Hasankhani, R. 2008. Studying of potato physical properties by means of machine vision (in
Persian). In Proc. 5th National Congress on Agricultural Machinery Engineering and
Mechanization, Ferdowsi University of Mashhad, Iran.
Jain, R. K., and S. Bal. 1997. Properties of pearl millet. Journal of Agricultural Engineering
Research, 66(2): 85-91.
Kibar, H., and T. Öztürk. 2008. Physical and mechanical properties of soybean. International
Agrophysics, 22: 239-244.
Kupferman, E. 2006. Minimizing bruising in apples. Postharvest Information Network,
Washington State University, Tree Fruit Research and Extension Center.
Lak, M. B., S. Minaei, J. Amiriparian, and B. Beheshti. 2010. Apple fruits recognition under
natural luminance using machine vision. Advance Journal of Food Science and Technology,
2(6): 325-327.
MATLAB. 2007. Image processing toolbox help.
Meisami-asl, E., S. Rafiee, A. Keyhani, and A. Tabatabaeefar. 2009. Some physical properties
of apple cv. ‘Golab’. CIGR Journal, 11, 6, Manuscript 1124.
Nieuwenhuizen, A. T., L. Tang, J. W. Hofstee, J. Muller, and E. J. V. Henten. 2007. Colour
based detection of volunteer potatoes as weeds in sugar beet fields using machine vision.
Precision Agriculture, 8: 267–278.
Rashidi, M., and K. Seyfi. 2007. Classification of fruits shape in cantaloupe using the analysis
of geometrical attributes. World Journal of Agricultural Science, 3(6): 735-740.
Rao, P. S., and S. Renganathan. 2002. New approaches for size determination of apple fruits for
automatic sorting and grading. Iranian Journal of Electrical and Computer Engineering. 1(2):
90-97.
Studman, C. J. 2001. Computers and electronics in postharvest technology - a review.
Computers and Electronics in Agriculture, 30: 109-124.
Zarifneshat, S., H. R. Ghassemzadeh, M. Sadeghi, M. H. Abbaspour-Fard, E. Ahmadi, A. Javadi,
and M. T. Shervani-Tabar. 2010. Effect of impact level and fruit properties on Golden
Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering
International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825.
8
Delicious apple bruising. American Journal of Agricultural and Biological Sciences, 5 (2):
114-121.
Zion, B., A. Shklyar, and I. Karplus. 1999. Sorting fish by computer vision. Computers and
Electronics in Agriculture, 23: 175-187.

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1825 4925-1-pb

  • 1. Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825. 1 Geometric properties of Kohanz apple fruits Mohammad Bagher Lak (Young Researchers Club, Science and Research Branch, Islamic Azad University, Tehran, Iran) Abstract: Kohanz is a domestic apple variety which is grown in Iran. It is sensitive to packing conditions. Bad packages normally cause decline in its quality. Therefore, apple’s geometric properties are of important consideration in the design of the fruit’s packaging facilities. In this study, a sample of 38 freshly harvested apple fruits was obtained, 82 images of their sides were acquired and geometric dimensions were measured. Their axial dimensions, equivalent diameter and sphericity were obtained using a vernier caliper with accuracy of 0.05 mm, while the cross section area, eccentricity, perimeter and roundness were measured using a color based image processing method. Their arithmetic mean diameter was 57.6 mm, while the mean eccentricity was 0.3058, mean roundness was 0.5858 and mean sphericity was 0.9985. Therefore, the packing design must be collections of spheroid spaces with diameters of about 6.8 mm which will include all of the apples. Keywords: eccentricity, equivalent diameter, image processing, roundness, sphericity 1. Introduction Among all the fruits produced in Iran, apple is the most important economical and industrial fruit (Meisami-asl et al, 2009). Kohanz apple is one of the famous Iranian domestic apple varieties. The fruits are currently filled in woody or plastic made boxes without any arrangement. The packages usually include some damaged fruits. Bruise damage is a major cause of fruit quality loss (Zarifneshat et al., 2010). The packing method causes compression damage in which fruit are bruised as they are pushed into a bin or bag (Kupferman, 2006). Conformity of size is particularly desirable for packaging and display purposes (Studman, 2001). Therefore, apples should be sorted into categories in order to provide better markets. The sorting method can be size-based in which they are classified according to their geometric properties. Aviara et al. (2007), Hasankhani (2008), Amiriparian et al. (2008), Meisami-asl et al. (2009), and Zarifneshat et al. (2010) worked on estimation of some agricultural products physical properties. Application of image processing based methods in agricultural activities has been developed for years. The applications involve activities such as auto-guidance (Benson et al., 2003; Han et al., 2004), weed control (Nieuwenhuizen et al., 2007; Ghazali et al., 2009), harvesting (Lak et al., 2010; Bulanon and Kataoka, 2010), yield monitoring (Chinchuluun et al., 2007; Annamalai, 2004) and post harvest (Amiriparian et al., 2008; Rao and Renganathan, 2002; Zion et al., 1999).
  • 2. Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825. 2 Geometric properties of fruits can be investigated by machine vision based methods (Rao and Renganathan, 2002; Rashidi and Seyfi, 2007). Aviara et al. (2007) determined physical properties of guna fruits; Davies (2010) investigated the physical properties of arigo seeds; and Hasankhani (2008) studied some geometric properties (area, volume, shape, external defects such as: greening, cracks and insect attack defects) of potato using machine vision. Amiriparian et al. (2008) estimated three agricultural products’ (apple (Golden Delicious), pistachio and onion) volume using image processing. It is likely that consumer demand for improved quality, longer storage life and guaranteed product safety will continue to grow (Studman, 2001). Therefore, providing an appropriate package will promote Kohanz apple marketing. The main objective of this study is to determine the freshly harvested Kohanz apple’s geometric properties. The axial dimensions, namely, length L (maximum dimension), thickness T (medium dimension) and width W (minimum dimension) were measured manually, meanwhile, cross sectional areas (pixels included in detected feature), perimeters (pixels surrounding detected feature), eccentricities (the ratio of the distance between the foci of the ellipse and its major axis length ( 10   and  circle = 0) (Gonzalez, et al., 2004), equivalent diameters (the diameter of a circle with the same area as the region (Gonzalez, et al., 2004), and roundness of sides of the fruits are the properties which can be defined using image processing. Sphericity was calculated using manually measured quantities. Good packaging would vouch for better marketing. While, identification of fruits’ geometric properties is required to design appropriate package size. Therefore, the main goal of this study is to define the optimum spheroid packing size for Kohanz apples using its geometric properties. 2. Materials and Methods Geometric properties of Kohanz apples were divided into two categories: parameters which could be measured using a vernier caliper; and properties that can be extracted from processed images. 2.1 Manual measured parameters A sample of 38 apples was selected randomly from a grove in Hamedan, western Iran. The axial dimensions, namely, length L, thickness T, and width W were measured using a vernier caliper (TAKA Vernier Caliper, 200×0.05mm). Arithmetic mean diameter Da, and sphericity  were calculated using Equation (1) and (2) as follows (Kibar and Öztürk, 2008; Jain and Bal, 1997). 3 WTL Da   (1) Where: D a= arithmetic mean diameter (mm), W = width (mm), T = thickness (mm), and L = length (mm)
  • 3. Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825. 3 3 2 )2( L WTLWT   (2) Where:  = sphericity (dimensionless) 2.2 Image processing extracted properties A digital camera (Sony, DSC-H5, Color CCD Camera) was used to acquire 82 images of 38 apples’ sides. At least, two sides of each apple were imaged. Format of the images was jpeg and they were in RGB (red-green-blue) color space. Because some of the samples were not symmetric, they were imaged from more than two sides. The images were converted to L*a*b color space. The L*a*b* space consists of a luminosity layer L*, chromaticity layer a* indicating where color falls along the red-green axis, and chromaticity layer b* indicating where the color falls along the blue-yellow axis (Matlab, 2007). Then, they were converted to binary form, noise-reduced, labeled, and the properties were extracted. The properties were: area, eccentricity and perimeter. Area and perimeter were in terms of pixel and eccentricity was dimensionless. Roundness was estimated using the relationship between area and perimeter (Equation (3)) and it was also dimensionless. 2 4 P A R   (MATLAB, 2007) (3) Where: R = roundness (dimensionless), A = area (pixel), and P = perimeter (pixel). 3. Results and Discussion Apples’ length, thickness and width were measured; therefore their equivalent diameter and sphericity were calculated by the data. Table 1 shows the descriptive statistics of properties which were measured by means of a caliper. All the apples were imaged at least with two sides (Figure 1). First, the images were converted to L*a*b color space (Figure 2), then they were converted to binary form (Figure 3). Finally, they were noise-reduced and some properties were extracted (Figure 4). Area, eccentricity and perimeter were the properties extracted from processed images. The roundness was calculated by
  • 4. Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825. 4 using a function between area and perimeter (Equation (3)). The descriptive statistics of apples’ properties which obtained from image processing are listed in Table 2. a b Figure 1 Typical original images acquired from two sides of apples a b Figure 2 Images in L*a*b color space
  • 5. Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825. 5 a b Figure 3 Binary images a b Figure 4 Noise-reduced binary images Table 1 Descriptive statistics of manually measured properties of apples Properties Na Range Minimum Maximum Mean Std. Deviation Variance Lb 82 17.45 49.65 67.10 60.05 3.0189 9.114 Tc 82 15.50 49.50 65.00 57.99 2.9438 8.666 Wd 82 13.50 47.00 60.50 54.83 3.1641 10.011 Da e 82 15.48 48.72 64.20 57.62 1.7572 3.088 a Sample size b Length in millimeter c Thickness in millimeter d Width in millimeter e Arithmetic mean diameter in millimeter
  • 6. Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825. 6 Table 2 Descriptive statistics of the properties measured by image processing N Range Minimum Maximum Mean Std. Deviation Variance Area (pixels) 82 1014172 1044468 2058640 1494828.10 204750.905 4.192E10 Eccentricity (pixels) 82 0.6758 0.0446 0.7204 0.3058 0.1116 0.012 Equivalent Diameter (pixels) 82 15.03 48.72 63.75 57.63 2.8285 8.000 Perimeter (pixels) 82 13130.5 4080.5 17211.0 6321.7 2239.0 5013152.3 Roundness (dimensionless) 82 0.7881 0.0526 0.8407 0.5858 0.2396 0.057 Sphericity (dimensionless) 82 0.0051 0.9948 0.9999 0.9985 0.0012 0.000 Mean and range of length, thickness, width, eccentricity, equivalent diameter, roundness and sphericity were 60.05[49.65 67.10], 57.99[49.50 65.00], 54.83[47.00 60.50], 0.3058 [0.0446 0.7204], 57.63[48.72 63.75], 0.5858  [0.0526 0.8407], and 0.9985  [0.9948 0.9999] respectively (Table 1 and Table 2). Extracted geometric properties of Kohanz apples were of at least two sides of each apple, therefore, the properties involve three dimension properties of them. The maximum, mean and minimum diameters of Golab apple were 65.04, 53.50 and 35.14 mm respectively (Meisami-asl, 2009); meanwhile the measures were 64.20, 57.62, and 48.72 mm for Kohanz variety. The apples’ sphericity ranges show that the apples can be considered as spheres with diameters equal to equivalent diameters. On the other hand, their maximum dimension is their length. Therefore, their packing design must be collections of spheroid spaces with diameters of about 68 mm which includes all of them. 4. Conclusions This paper considered Kohanz apple’s geometric properties. Their length, thickness and width were measured by caliper. Their equivalent diameters and sphericity were calculated. Their area, perimeter and eccentricity were extracted by image processing and roundness was computed by a function with area and perimeter. Finally it was determined that a collection of spheroid spaces with diameters of about 68 mm will be the most appropriate package design. References Amiriparian, J., M. H. Khoshtaghaza, and E. Kabir. 2008. A practical model for estimation of agricultural products volume using machine vision (in Persian). In Proc. 5th National Congress on Agricultural Machinery Engineering and Mechanization, Ferdowsi University of Mashhad, Iran. Annamalai, P. 2004. Citrus yield mapping system using machine vision. M.S. Thesis, Department of Agricultural and Biological Engineering, University of Florida. 81.
  • 7. Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825. 7 Aviara, N. A, S. K. Shittu, and M. A. Haque. 2007. Physical properties of guna fruits relevant in bulk handling and mechanical processing. International Agrophysics, 21(1): 7-16. Benson, E. R., J. F. Reid, and Q. Zhang. 2003. Machine vision-based guidance system for agricultural grain harvester using cut-edge detection. Biosystems Engineering, 86 (4), 389– 398. Bulanon, D. M., and T. Kataoka . 2010. Fruit detection system and an end effector for robotic harvesting of Fuji apples. CIGR Journal, 12(1): 203-210. Chinchuluun, R., W. S. Lee, and R. Ehsani. 2007. Citrus yield mapping system on a canopy, shake and catch harvester. In Proc. ASABE Annual International Meeting, Paper Number: 073050. Davies, R. M. 2010. Some physical properties of arigo seeds. International Agrophysics, 24(1): 89-92. Ghazali, K. H, M. M. Mustafa, and A. Hussain. 2009. Machine vision system for automatic weeding strategy in oil palm plantation using image filtering technique. International Journal of Electrical, Computer, and Systems Engineering 3:4, 193-197. Gonzalez, R. C., R. E. Woods, and S. L. Eddins. 2004. Digital image processing using MATLAB. Pearson Education. 609 p. Han, S., Q. Zhang, B. Ni, and J. F. Reid. 2004. A guidance directrix approach to vision-based vehicle guidance systems. Computers and Electronics in Agriculture, 43: 179-195. Hasankhani, R. 2008. Studying of potato physical properties by means of machine vision (in Persian). In Proc. 5th National Congress on Agricultural Machinery Engineering and Mechanization, Ferdowsi University of Mashhad, Iran. Jain, R. K., and S. Bal. 1997. Properties of pearl millet. Journal of Agricultural Engineering Research, 66(2): 85-91. Kibar, H., and T. Öztürk. 2008. Physical and mechanical properties of soybean. International Agrophysics, 22: 239-244. Kupferman, E. 2006. Minimizing bruising in apples. Postharvest Information Network, Washington State University, Tree Fruit Research and Extension Center. Lak, M. B., S. Minaei, J. Amiriparian, and B. Beheshti. 2010. Apple fruits recognition under natural luminance using machine vision. Advance Journal of Food Science and Technology, 2(6): 325-327. MATLAB. 2007. Image processing toolbox help. Meisami-asl, E., S. Rafiee, A. Keyhani, and A. Tabatabaeefar. 2009. Some physical properties of apple cv. ‘Golab’. CIGR Journal, 11, 6, Manuscript 1124. Nieuwenhuizen, A. T., L. Tang, J. W. Hofstee, J. Muller, and E. J. V. Henten. 2007. Colour based detection of volunteer potatoes as weeds in sugar beet fields using machine vision. Precision Agriculture, 8: 267–278. Rashidi, M., and K. Seyfi. 2007. Classification of fruits shape in cantaloupe using the analysis of geometrical attributes. World Journal of Agricultural Science, 3(6): 735-740. Rao, P. S., and S. Renganathan. 2002. New approaches for size determination of apple fruits for automatic sorting and grading. Iranian Journal of Electrical and Computer Engineering. 1(2): 90-97. Studman, C. J. 2001. Computers and electronics in postharvest technology - a review. Computers and Electronics in Agriculture, 30: 109-124. Zarifneshat, S., H. R. Ghassemzadeh, M. Sadeghi, M. H. Abbaspour-Fard, E. Ahmadi, A. Javadi, and M. T. Shervani-Tabar. 2010. Effect of impact level and fruit properties on Golden
  • 8. Mohammad Bagher Lak. Geometric properties of Kohanz apple fruits. Agricultural Engineering International: CIGR Journal. Vol.13, No.4, 2011. Manuscript No. 1825. 8 Delicious apple bruising. American Journal of Agricultural and Biological Sciences, 5 (2): 114-121. Zion, B., A. Shklyar, and I. Karplus. 1999. Sorting fish by computer vision. Computers and Electronics in Agriculture, 23: 175-187.