2013
DOI: 10.1007/s40003-013-0057-7
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Development of a New Threshold Based Classification Model for Analyzing Thermal Imaging Data to Detect Fungal Infection of Pistachio Kernel

Abstract: Thermal images have beneficial information which can be used for diagnostic purposes. The information can be released by applying appropriate analyses methods. In this research, a new algorithm, threshold based classification (TBC), was developed to analyze thermal images of healthy and fungal-infected pistachio kernels in MATLAB 2010A environment. Results showed that TBC algorithm can classify successfully healthy and infected pistachio kernels without considering the infection stages.

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Cited by 12 publications
(6 citation statements)
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“…Bruises take color accurate to the force value (Cubero et al 2011;Menesatti et al 2009). Therefore, a non-destructive method to detect damages which is based on a thermovision camera was used (Kheiralipour et al 2013). Research conducted by Doosti-Irani et al (2016) follows that the thermal imaging system allows to determine the relationship between inside and outside temperatures of destructed tissue.…”
Section: Introductionmentioning
confidence: 99%
“…Bruises take color accurate to the force value (Cubero et al 2011;Menesatti et al 2009). Therefore, a non-destructive method to detect damages which is based on a thermovision camera was used (Kheiralipour et al 2013). Research conducted by Doosti-Irani et al (2016) follows that the thermal imaging system allows to determine the relationship between inside and outside temperatures of destructed tissue.…”
Section: Introductionmentioning
confidence: 99%
“…These researchers often classify damage as visible permanent deformations (Sargent et al, 1989) or externally visible skin cracking and rupture (Geyer et al, 2002). Techniques to analyze damaged fruits with a nondestructive method have used thermal imaging devices (Cui et al, 2017a;Kheiralipour et al, 2013). Doosti-Irani et al (2016) used a thermal imaging camera to assess the relationship between the deep internal temperatures of tested fruit and the external temperatures at the point where bruising appeared using thermal maps and thermal bruise depth.…”
mentioning
confidence: 99%
“…Similarly, Kheiralipour et al (2013) tried to detect fungal infection in pistachio kernels infected by an aflatoxin-producing A. flavus isolate R5 and non-aflatoxin-producing isolate KK11 using an active thermal imaging system. Thermal images were acquired for both healthy and infected seeds before heating, directly after heating at 90°C for 90s and after being cooled at room temperature for 10s.…”
Section: Detection Of Fungal Infectionsmentioning
confidence: 99%