Design of Sesame Peeling Machine and Performance Analysis with Threshold-Based Image Segmentation Technique

Year 2024, , 38 - 44, 30.06.2024

Ahmet Gündoğdu , Emrullah Acar , Reşat Çelikel

https://doi.org/10.36222/ejt.1448580

Abstract

In this study, peeled sesame seeds were analyzed using a threshold-based image segmentation technique. Peeled sesame seeds were obtained from a sesame membrane
peeling machine whose design and production was carried out within the project's scope. By applying the image segmentation technique to the samples taken from the machine, the
machine's sesame peeling performance and sesame peeling percentage were determined. Automatic calculation of the peeled sesame weights in the image is presented by the
threshold-based image segmentation technique, which is one of the basic operations of digital image processing and is extensively employed in many application areas, including
extraction, detection, and identification of features. This technique aims to divide an image into meaningful regions according to a particular operation. Based on the results obtained
using the threshold-based image segmentation technique, the success achieved in the peeling process is 48%, 56%, 60% for periods of 60 min, 120 min, 180 min respectively. By using
the designed machine, the processing time of peeling sesame has been reduced by 75%, water consumption has been reduced by 90%, and salt use has been eliminated. Moreover, operating, personnel, and energy costs have been minimized.

Keywords

Sesame, Sesame Peeling Machine, Machine Design, Image Processing

Supporting Institution

Ministry of Science, Industry and Technology

Project Number

0905.STZ.2015

Thanks

This study is supported by Ministry of Science, Industry and Technology/Turkey with 0905.STZ.2015 numbered project, titled “Design and Manufacture of Technological Sesame Peeling Machine”. Thanks for support.

References

• [1] Carbonell-Barrachina AA, Lluch MA, Perez-Munera I, Hernando I, Castillo S (2009) Effect of chemical dehulling of sesame on color and microstructure. Food Sciences and Technology International 15(3): 229-234.
• [2] Tunde-Akintunde TY, Oke MO, Akintunde BO (2012) Sesame Seed, Oilseeds, Dr. Uduak G. Akpan (Ed.), ISBN: 978-953-51-0665-4, InTech, Available from: http://www.intechopen.com/books/oilseeds/sesameseed
• [3] Akbulut M (2008) Comparative studies of mineral contents of hulled sesame paste (tahin), unhulled sesame paste (bozkır tahin) and their blends. Asian Journal of Chemistry 20(3):1801-1805.
• [4] Röbbelen G, Downey RK. Ashri A (1989) Oil Crops of the World-their Breeding & Utilization. Mc Graw-Hill Publishing Company.
• [5] Yehia G, Moharram-Hussein OA, Osman IA, Yaldes IA, Abou-EI-Khier, Wet decortications of sesame seeds by new methods. United Nations University Website, http://unu.eduarchive.unu.edu/unupress/food/8F121e/8F121E09.htm
• [6] Suzanne L (1988) Produce Peeling Machine Particularly for Shelling Nuts, (November 22 1988 4785729 USA patent).
• [7] Lee KS, Noh HK (2015) Development of threshing machine for shatter-resistant sesame. Journal of Biosystems Engineering 40(2):110-114.
• [8] Srinivas GL, Singh SP, Javed A (2020) Experimental evaluation of topologically optimized manipulator-link using PLC and HMI based control system. Materials Today: Proceedings. https://doi.org/10.1016/j.matpr.2020.08.023
• [9] Baladhandabany D, Gowtham S, Kowsikkumar T, Gomathi P, Vijayasalini P (2015) PLC based automatic liquid filling system. International Journal of Computer Science and Mobile Computing 4(3):684-692.
• [10] Prinsloo G, Dobson R, Schreve K (2014) Carbon footprint optimization as PLC control strategy in solar power system automation. Energy Procedia 49:2180-2190.
• [11] Papoutsidakis M, Xatzopoulos A, Smyraiou GP, Tseles D (2017) PLC Programming Case Study for Hydraulic Positioning Systems Implementations. International Journal of Computer Applications, 167(12):49-53.
• [12] Das R, Dutta S, Sarkar A, Samanta K (2013) Automation of tank level using Plc and establishment of Hmi by Scada. IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) 7(2):61-67.
• [13] Maraba V, Kuzucuoğlu A (2011) PID neural network based speed control of asynchronous motor using programmable logic controller. Advances in Electrical and Computer Engineering 11(4):23-28.
• [14] Ahiska R, Mamur H (2012) A test system and supervisory control and data acquisition application with programmable logic controller for thermoelectric generators. Energy conversion and management 64:15-22.
• [15] Bayindir R, Cetinceviz Y (2011) A water pumping control system with a programmable logic controller (PLC) and industrial wireless modules for industrial plants-An experimental setup. ISA transactions. 50(2):321-328.
• [16] Mocanu DA, Bădescu V, Bucur C, Ștefan I, Carcadea E, Răboacă MS, Manta I (2020) PLC Automation and Control Strategy in a Stirling Solar Power System. Energies 13(8):1-19.
• [17] Singh R, Verma HK (2018) Development of PLC-based controller for pneumatic pressing machine in engine-bearing manufacturing plant. Procedia Computer Science 125:449-458.
• [18] Pratap KA, Marjorie SR, Saikumar M (2020) Automatic vegetable chopper using image processing. Materials Today: Proceedings 33(7):4787-4789.
• [19] Choi JY, Moon KD (2020) Non-destructive discrimination of sesame oils via hyperspectral image analysis. Journal of Food Composition and Analysis 90:103505.
• [20] Fermo IR, Cavali TS, Bonfim-Rocha L, Srutkoske CL, Flores FC, Andrade CM (2020) Development of a low-cost digital image processing system for oranges selection using hopfield networks. Food and Bioproducts Processing 125:181-192.
• [21] Nasir M, Attique Khan M, Sharif M, Lali IU, Saba T, Iqbal T (2018) An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach. Microscopy research and technique 81(6):528-543.
• [22] Norton KA, Iyatomi H, Celebi ME, Schaefer G, Tanaka M, Ogawa K (2010) Development of a novel border detection method for melanocytic and non‐melanocytic dermoscopy images. In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.
• [23] Garnavi R, Aldeen M, Celebi ME, Varigos G, Finch S (2011) Border detection in dermoscopy images using hybrid thresholding on optimized color channels. Computerized Medical Imaging and Graphics 35(2):105–115.
• [24] Satheesha T, Satyanarayana D, Giriprasad M, Nagesh K (2016) Detection of melanoma using distinct features. In 2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC), IEEE.
• [25] Abbas Q, Fondón I, Rashid M (2011) Unsupervised skin lesions border detection via two‐dimensional image analysis. Computer Methods and Programs in Biomedicine 104(3):e1-e15.
• [26] Do TT, Zhou Y, Zheng H, Cheung NM, Koh D (2014) Early melanoma diagnosis with mobile imaging. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE.
• [27] Sadri AR, Zekri M, Sadri S, Gheissari N, Mokhtari M, Kolahdouzan F (2013) Segmentation of dermoscopy images using wavelet networks. IEEE Transactions on Biomedical Engineering 60(4):1134-1141.
• [28] Saez A, Serrano C, Acha B (2014) Model‐based classification methods of global patterns in dermoscopic images. IEEE Transactions on Medical Imaging 33(5):1137-1147.
• [29] Zhou H, Schaefer G, Sadka AH, Celebi ME (2009) Anisotropic mean shift based fuzzy c‐means segmentation of dermoscopy images. IEEE Journal of Selected Topics in Signal Processing 3(1):26-34.
• [30] Kabade Rohit S, Gaikwad M (2013) Segmentation of brain tumour and its area calculation in brain MR images using K-mean clustering and fuzzy C-mean algorithm. International Journal of Computer Science & Engineering Technology 4(05):524-531.
• [31] Girgis MF, Method for Peeling and Processing Grain, (December 31 1968- 3419056 patent).
• [32] Dopp S, Device for the Wet Treating of Seed Material, (December 16 1986-4628807 patent).
• [33] Beeler ML, Peeler with Inclined Grooves in Side Wall, (April 8 1997-5617783 patent).
• [34] Demir Z (2019) Susam Zarı Soyma Makinasının Tasarımı, Firat University Journal of Engineering Science 31(1):241-248.
• [35] Raid AM, Khedr WM, El-Dosuky MA, Aoud M (2014) Image restoration based on morphological operations. International Journal of Computer Science, Engineering and Information Technology (IJCSEIT) 4(3):9-21.
• [36] Patel S, Trivedi P, Gandhi V, Prajapati GI (2013) 2D basic shape detection using region properties. International Journal of Engineering Research & Technology 2(5):1147-1153.