Non-destructive robotic sorting of cracked pistachio using deep learning

Pistachio, an agricultural product, is considered one of the guilt-free snacks due to its nutritional content, taste, and its health benefits. Usually, when it is consumed as a snack, in-shell pistachios are more desirable, whereas pistachios without their shell are ordinarily used for food preparat...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Karadağ, Ahmet Emin [verfasserIn] Kılıç, Ali [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Deep learning Object detection Robotic sorting system

Übergeordnetes Werk:	Enthalten in: Postharvest biology and technology - Amsterdam [u.a.] : Elsevier Science, 1991, 198
Übergeordnetes Werk:	volume:198

DOI / URN:	10.1016/j.postharvbio.2022.112229

Katalog-ID:	ELV009200185

Internformat


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520			\|a Pistachio, an agricultural product, is considered one of the guilt-free snacks due to its nutritional content, taste, and its health benefits. Usually, when it is consumed as a snack, in-shell pistachios are more desirable, whereas pistachios without their shell are ordinarily used for food preparation. One parameter important for pistachios sold as a snack is whether their shell is open. In pistachio processing plants, closed-shelled pistachios are separated with manual labor. There also exists an automated method called pin-picker machines, but as these machines harm pistachio kernels, they are undesirable. This paper offers a method to separate open-shelled pistachios from closed-shelled pistachios in an unharmful method. This method is done by using a deep learning-based object detection algorithm. In order to sort pistachios physically, a gripper and a conveyor system equipped Cartesian manipulator has been developed. In addition, a double-camera configuration is used. The key function of a double-camera configuration is to see the one-sided split on pistachios, which is hard to achieve with a single-camera configuration. Firstly, the object detection algorithm detects pistachios and gives their position with bounding boxes. Then their real-world coordinates are calculated, pistachios in both images taken with the cameras are paired, and the Cartesian manipulator separates pistachios. The detection accuracy was found as 98 % and 85 % for open-shelled pistachio and closed-shelled pistachio, respectively. With this method, closed-shelled pistachios can be sent to a cracking machine, or they can be sent to be stored for later use as they can withstand environmental effects better than open-shelled pistachios.
650		4	\|a Deep learning
650		4	\|a Object detection
650		4	\|a Robotic sorting system
700	1		\|a Kılıç, Ali \|e verfasserin \|4 aut
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allfields	10.1016/j.postharvbio.2022.112229 doi (DE-627)ELV009200185 (ELSEVIER)S0925-5214(22)00397-0 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl Karadağ, Ahmet Emin verfasserin aut Non-destructive robotic sorting of cracked pistachio using deep learning 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Pistachio, an agricultural product, is considered one of the guilt-free snacks due to its nutritional content, taste, and its health benefits. Usually, when it is consumed as a snack, in-shell pistachios are more desirable, whereas pistachios without their shell are ordinarily used for food preparation. One parameter important for pistachios sold as a snack is whether their shell is open. In pistachio processing plants, closed-shelled pistachios are separated with manual labor. There also exists an automated method called pin-picker machines, but as these machines harm pistachio kernels, they are undesirable. This paper offers a method to separate open-shelled pistachios from closed-shelled pistachios in an unharmful method. This method is done by using a deep learning-based object detection algorithm. In order to sort pistachios physically, a gripper and a conveyor system equipped Cartesian manipulator has been developed. In addition, a double-camera configuration is used. The key function of a double-camera configuration is to see the one-sided split on pistachios, which is hard to achieve with a single-camera configuration. Firstly, the object detection algorithm detects pistachios and gives their position with bounding boxes. Then their real-world coordinates are calculated, pistachios in both images taken with the cameras are paired, and the Cartesian manipulator separates pistachios. The detection accuracy was found as 98 % and 85 % for open-shelled pistachio and closed-shelled pistachio, respectively. With this method, closed-shelled pistachios can be sent to a cracking machine, or they can be sent to be stored for later use as they can withstand environmental effects better than open-shelled pistachios. Deep learning Object detection Robotic sorting system Kılıç, Ali verfasserin aut Enthalten in Postharvest biology and technology Amsterdam [u.a.] : Elsevier Science, 1991 198 Online-Ressource (DE-627)306590085 (DE-600)1498582-2 (DE-576)259484180 1873-2356 nnns volume:198 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.34 Lebensmitteltechnologie VZ 48.59 Pflanzenproduktion: Sonstiges VZ AR 198
spelling	10.1016/j.postharvbio.2022.112229 doi (DE-627)ELV009200185 (ELSEVIER)S0925-5214(22)00397-0 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl Karadağ, Ahmet Emin verfasserin aut Non-destructive robotic sorting of cracked pistachio using deep learning 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Pistachio, an agricultural product, is considered one of the guilt-free snacks due to its nutritional content, taste, and its health benefits. Usually, when it is consumed as a snack, in-shell pistachios are more desirable, whereas pistachios without their shell are ordinarily used for food preparation. One parameter important for pistachios sold as a snack is whether their shell is open. In pistachio processing plants, closed-shelled pistachios are separated with manual labor. There also exists an automated method called pin-picker machines, but as these machines harm pistachio kernels, they are undesirable. This paper offers a method to separate open-shelled pistachios from closed-shelled pistachios in an unharmful method. This method is done by using a deep learning-based object detection algorithm. In order to sort pistachios physically, a gripper and a conveyor system equipped Cartesian manipulator has been developed. In addition, a double-camera configuration is used. The key function of a double-camera configuration is to see the one-sided split on pistachios, which is hard to achieve with a single-camera configuration. Firstly, the object detection algorithm detects pistachios and gives their position with bounding boxes. Then their real-world coordinates are calculated, pistachios in both images taken with the cameras are paired, and the Cartesian manipulator separates pistachios. The detection accuracy was found as 98 % and 85 % for open-shelled pistachio and closed-shelled pistachio, respectively. With this method, closed-shelled pistachios can be sent to a cracking machine, or they can be sent to be stored for later use as they can withstand environmental effects better than open-shelled pistachios. Deep learning Object detection Robotic sorting system Kılıç, Ali verfasserin aut Enthalten in Postharvest biology and technology Amsterdam [u.a.] : Elsevier Science, 1991 198 Online-Ressource (DE-627)306590085 (DE-600)1498582-2 (DE-576)259484180 1873-2356 nnns volume:198 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.34 Lebensmitteltechnologie VZ 48.59 Pflanzenproduktion: Sonstiges VZ AR 198
allfields_unstemmed	10.1016/j.postharvbio.2022.112229 doi (DE-627)ELV009200185 (ELSEVIER)S0925-5214(22)00397-0 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl Karadağ, Ahmet Emin verfasserin aut Non-destructive robotic sorting of cracked pistachio using deep learning 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Pistachio, an agricultural product, is considered one of the guilt-free snacks due to its nutritional content, taste, and its health benefits. Usually, when it is consumed as a snack, in-shell pistachios are more desirable, whereas pistachios without their shell are ordinarily used for food preparation. One parameter important for pistachios sold as a snack is whether their shell is open. In pistachio processing plants, closed-shelled pistachios are separated with manual labor. There also exists an automated method called pin-picker machines, but as these machines harm pistachio kernels, they are undesirable. This paper offers a method to separate open-shelled pistachios from closed-shelled pistachios in an unharmful method. This method is done by using a deep learning-based object detection algorithm. In order to sort pistachios physically, a gripper and a conveyor system equipped Cartesian manipulator has been developed. In addition, a double-camera configuration is used. The key function of a double-camera configuration is to see the one-sided split on pistachios, which is hard to achieve with a single-camera configuration. Firstly, the object detection algorithm detects pistachios and gives their position with bounding boxes. Then their real-world coordinates are calculated, pistachios in both images taken with the cameras are paired, and the Cartesian manipulator separates pistachios. The detection accuracy was found as 98 % and 85 % for open-shelled pistachio and closed-shelled pistachio, respectively. With this method, closed-shelled pistachios can be sent to a cracking machine, or they can be sent to be stored for later use as they can withstand environmental effects better than open-shelled pistachios. Deep learning Object detection Robotic sorting system Kılıç, Ali verfasserin aut Enthalten in Postharvest biology and technology Amsterdam [u.a.] : Elsevier Science, 1991 198 Online-Ressource (DE-627)306590085 (DE-600)1498582-2 (DE-576)259484180 1873-2356 nnns volume:198 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.34 Lebensmitteltechnologie VZ 48.59 Pflanzenproduktion: Sonstiges VZ AR 198
allfieldsGer	10.1016/j.postharvbio.2022.112229 doi (DE-627)ELV009200185 (ELSEVIER)S0925-5214(22)00397-0 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl Karadağ, Ahmet Emin verfasserin aut Non-destructive robotic sorting of cracked pistachio using deep learning 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Pistachio, an agricultural product, is considered one of the guilt-free snacks due to its nutritional content, taste, and its health benefits. Usually, when it is consumed as a snack, in-shell pistachios are more desirable, whereas pistachios without their shell are ordinarily used for food preparation. One parameter important for pistachios sold as a snack is whether their shell is open. In pistachio processing plants, closed-shelled pistachios are separated with manual labor. There also exists an automated method called pin-picker machines, but as these machines harm pistachio kernels, they are undesirable. This paper offers a method to separate open-shelled pistachios from closed-shelled pistachios in an unharmful method. This method is done by using a deep learning-based object detection algorithm. In order to sort pistachios physically, a gripper and a conveyor system equipped Cartesian manipulator has been developed. In addition, a double-camera configuration is used. The key function of a double-camera configuration is to see the one-sided split on pistachios, which is hard to achieve with a single-camera configuration. Firstly, the object detection algorithm detects pistachios and gives their position with bounding boxes. Then their real-world coordinates are calculated, pistachios in both images taken with the cameras are paired, and the Cartesian manipulator separates pistachios. The detection accuracy was found as 98 % and 85 % for open-shelled pistachio and closed-shelled pistachio, respectively. With this method, closed-shelled pistachios can be sent to a cracking machine, or they can be sent to be stored for later use as they can withstand environmental effects better than open-shelled pistachios. Deep learning Object detection Robotic sorting system Kılıç, Ali verfasserin aut Enthalten in Postharvest biology and technology Amsterdam [u.a.] : Elsevier Science, 1991 198 Online-Ressource (DE-627)306590085 (DE-600)1498582-2 (DE-576)259484180 1873-2356 nnns volume:198 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.34 Lebensmitteltechnologie VZ 48.59 Pflanzenproduktion: Sonstiges VZ AR 198
allfieldsSound	10.1016/j.postharvbio.2022.112229 doi (DE-627)ELV009200185 (ELSEVIER)S0925-5214(22)00397-0 DE-627 ger DE-627 rda eng 570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl Karadağ, Ahmet Emin verfasserin aut Non-destructive robotic sorting of cracked pistachio using deep learning 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Pistachio, an agricultural product, is considered one of the guilt-free snacks due to its nutritional content, taste, and its health benefits. Usually, when it is consumed as a snack, in-shell pistachios are more desirable, whereas pistachios without their shell are ordinarily used for food preparation. One parameter important for pistachios sold as a snack is whether their shell is open. In pistachio processing plants, closed-shelled pistachios are separated with manual labor. There also exists an automated method called pin-picker machines, but as these machines harm pistachio kernels, they are undesirable. This paper offers a method to separate open-shelled pistachios from closed-shelled pistachios in an unharmful method. This method is done by using a deep learning-based object detection algorithm. In order to sort pistachios physically, a gripper and a conveyor system equipped Cartesian manipulator has been developed. In addition, a double-camera configuration is used. The key function of a double-camera configuration is to see the one-sided split on pistachios, which is hard to achieve with a single-camera configuration. Firstly, the object detection algorithm detects pistachios and gives their position with bounding boxes. Then their real-world coordinates are calculated, pistachios in both images taken with the cameras are paired, and the Cartesian manipulator separates pistachios. The detection accuracy was found as 98 % and 85 % for open-shelled pistachio and closed-shelled pistachio, respectively. With this method, closed-shelled pistachios can be sent to a cracking machine, or they can be sent to be stored for later use as they can withstand environmental effects better than open-shelled pistachios. Deep learning Object detection Robotic sorting system Kılıç, Ali verfasserin aut Enthalten in Postharvest biology and technology Amsterdam [u.a.] : Elsevier Science, 1991 198 Online-Ressource (DE-627)306590085 (DE-600)1498582-2 (DE-576)259484180 1873-2356 nnns volume:198 GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 58.34 Lebensmitteltechnologie VZ 48.59 Pflanzenproduktion: Sonstiges VZ AR 198
language	English
source	Enthalten in Postharvest biology and technology 198 volume:198
sourceStr	Enthalten in Postharvest biology and technology 198 volume:198
format_phy_str_mv	Article
bklname	Lebensmitteltechnologie Pflanzenproduktion: Sonstiges
institution	findex.gbv.de
topic_facet	Deep learning Object detection Robotic sorting system
dewey-raw	570
isfreeaccess_bool	false
container_title	Postharvest biology and technology
authorswithroles_txt_mv	Karadağ, Ahmet Emin @@aut@@ Kılıç, Ali @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	306590085
dewey-sort	3570
id	ELV009200185
language_de	englisch
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author	Karadağ, Ahmet Emin
spellingShingle	Karadağ, Ahmet Emin ddc 570 fid BIODIV bkl 58.34 bkl 48.59 misc Deep learning misc Object detection misc Robotic sorting system Non-destructive robotic sorting of cracked pistachio using deep learning
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topic_title	570 630 VZ BIODIV DE-30 fid 58.34 bkl 48.59 bkl Non-destructive robotic sorting of cracked pistachio using deep learning Deep learning Object detection Robotic sorting system
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title	Non-destructive robotic sorting of cracked pistachio using deep learning
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title_full	Non-destructive robotic sorting of cracked pistachio using deep learning
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title_sort	non-destructive robotic sorting of cracked pistachio using deep learning
title_auth	Non-destructive robotic sorting of cracked pistachio using deep learning
abstract	Pistachio, an agricultural product, is considered one of the guilt-free snacks due to its nutritional content, taste, and its health benefits. Usually, when it is consumed as a snack, in-shell pistachios are more desirable, whereas pistachios without their shell are ordinarily used for food preparation. One parameter important for pistachios sold as a snack is whether their shell is open. In pistachio processing plants, closed-shelled pistachios are separated with manual labor. There also exists an automated method called pin-picker machines, but as these machines harm pistachio kernels, they are undesirable. This paper offers a method to separate open-shelled pistachios from closed-shelled pistachios in an unharmful method. This method is done by using a deep learning-based object detection algorithm. In order to sort pistachios physically, a gripper and a conveyor system equipped Cartesian manipulator has been developed. In addition, a double-camera configuration is used. The key function of a double-camera configuration is to see the one-sided split on pistachios, which is hard to achieve with a single-camera configuration. Firstly, the object detection algorithm detects pistachios and gives their position with bounding boxes. Then their real-world coordinates are calculated, pistachios in both images taken with the cameras are paired, and the Cartesian manipulator separates pistachios. The detection accuracy was found as 98 % and 85 % for open-shelled pistachio and closed-shelled pistachio, respectively. With this method, closed-shelled pistachios can be sent to a cracking machine, or they can be sent to be stored for later use as they can withstand environmental effects better than open-shelled pistachios.
abstractGer	Pistachio, an agricultural product, is considered one of the guilt-free snacks due to its nutritional content, taste, and its health benefits. Usually, when it is consumed as a snack, in-shell pistachios are more desirable, whereas pistachios without their shell are ordinarily used for food preparation. One parameter important for pistachios sold as a snack is whether their shell is open. In pistachio processing plants, closed-shelled pistachios are separated with manual labor. There also exists an automated method called pin-picker machines, but as these machines harm pistachio kernels, they are undesirable. This paper offers a method to separate open-shelled pistachios from closed-shelled pistachios in an unharmful method. This method is done by using a deep learning-based object detection algorithm. In order to sort pistachios physically, a gripper and a conveyor system equipped Cartesian manipulator has been developed. In addition, a double-camera configuration is used. The key function of a double-camera configuration is to see the one-sided split on pistachios, which is hard to achieve with a single-camera configuration. Firstly, the object detection algorithm detects pistachios and gives their position with bounding boxes. Then their real-world coordinates are calculated, pistachios in both images taken with the cameras are paired, and the Cartesian manipulator separates pistachios. The detection accuracy was found as 98 % and 85 % for open-shelled pistachio and closed-shelled pistachio, respectively. With this method, closed-shelled pistachios can be sent to a cracking machine, or they can be sent to be stored for later use as they can withstand environmental effects better than open-shelled pistachios.
abstract_unstemmed	Pistachio, an agricultural product, is considered one of the guilt-free snacks due to its nutritional content, taste, and its health benefits. Usually, when it is consumed as a snack, in-shell pistachios are more desirable, whereas pistachios without their shell are ordinarily used for food preparation. One parameter important for pistachios sold as a snack is whether their shell is open. In pistachio processing plants, closed-shelled pistachios are separated with manual labor. There also exists an automated method called pin-picker machines, but as these machines harm pistachio kernels, they are undesirable. This paper offers a method to separate open-shelled pistachios from closed-shelled pistachios in an unharmful method. This method is done by using a deep learning-based object detection algorithm. In order to sort pistachios physically, a gripper and a conveyor system equipped Cartesian manipulator has been developed. In addition, a double-camera configuration is used. The key function of a double-camera configuration is to see the one-sided split on pistachios, which is hard to achieve with a single-camera configuration. Firstly, the object detection algorithm detects pistachios and gives their position with bounding boxes. Then their real-world coordinates are calculated, pistachios in both images taken with the cameras are paired, and the Cartesian manipulator separates pistachios. The detection accuracy was found as 98 % and 85 % for open-shelled pistachio and closed-shelled pistachio, respectively. With this method, closed-shelled pistachios can be sent to a cracking machine, or they can be sent to be stored for later use as they can withstand environmental effects better than open-shelled pistachios.
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title_short	Non-destructive robotic sorting of cracked pistachio using deep learning
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up_date	2024-07-06T22:20:37.265Z
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