Application of voice processing and artificial neural network in the separation of hazelnuts, based on size

Mahmoudi, Ehsan; Jafari, Seid Mahdi; Rahmanian Jahromi, Neda; Akbarian Meymand, Mohammad Javad; Vatankhah, Mehdi

doi:10.22101/JRIFST.2015.01.21.341

Application of voice processing and artificial neural network in the separation of hazelnuts, based on size

Document Type : Original Paper

Authors

Ehsan Mahmoudi ¹

Seid Mahdi Jafari ²

Neda Rahmanian Jahromi ¹

Mohammad Javad Akbarian Meymand ¹

Mehdi Vatankhah ³

¹ MSc. Graduated Student, Gorgan University of Agricaltural Science & Natural Resources, Gorgan, Iran

² Assistant Professor, Department of Food science and Technology, Gorgan University of Agricaltural Science & Natural Resources, Gorgan, Iran

³ MSc. Graduated Student, Sabzevar Branch, Islamic Azad University, Sabzevar, Iran

https://doi.org/10.22101/JRIFST.2015.01.21.341

Abstract

In this study, Clash Voice processing in the field of wavelet and Artificial neural network (ANN) has been evaluated in order to separate hazelnuts according to their size (large, small, medium), and also being filled or empty. Hazelnuts were divided into three size groups (large, medium and small) and each hazelnut of the groups was weighted in order to separate the filled ones from the empty ones. All hazelnuts were then released from 40 and 50 cm height; bopped with a metal plate and Clash Voice was recorded. Signals in the field of wavelet were processed after the Preprocessing. Obtained profiles were applied as input to the ANN. The results showed that Neural Networks with 3 and 9 neurons in the hidden layer could successfully (accuracy of 100%) break up the hazelnuts that were dropped from 40 and 50 cm heights. The filled and empty hazelnuts of large, medium and small groups were separated from each other with the accuracy of 100, 99.61 and 98% for the height of 40 cm and 100, 99.66, 97.5% for the height of 50 cm. This research in combination with the common methods could probably reduce damages; increase the precision and the speed of separation.

Keywords

Acoustic

Artificial Neural Network

Discrete Wavelet transform

Hazelnut

Separation

Sound

رستمی، ا.، غضنفری مقدم، ا.، طالبی، س. و سجادی، س. ج. 1387. تشخیص پسته‌‌ها‌‌ی پوک از مغز‌دار با استفاده از انعکاس و پردازش صدا در دو حوزه زمان و فرکانس. مجله تحقیقات مهندسی کشاورزی، 9: 123-134.

سجادی، س.، ج. غضنفری مقدم، ا. و رستمی، ا. 1388. ارزیابی یک سیستم هوشمند برای جدا‌‌سازی پسته با استفاده از شبکه‌‌ها‌‌ی عصبی مصنوعی (ANN) و تبدیل موجک انعکاس صدا. مجله مهندسی بیو‌سیستم ایران، 40: 155-161.

Cetin, A., Pearson, T. & Tewfik, A. 2004. Classification of closed-and open-shell pistachio nuts using voice-recognition technology. Transactions-American Society of Agricultural Engineers, 47: 659-664.

De Belie, N., Schotte, S., Lammertyn, J., Nicolai, B. & De Baerdemaeker, J. 2000. PH—postharvest technology: firmness changes of pear fruit before and after harvest with the acoustic impulse response technique. Journal of Agricultural Engineering Research, 77: 183-191.

Diezma-Iglesias, B., Ruiz-Altisent, M. & Barreiro, P. 2004. Detection of internal quality in seedless watermelon by acoustic impulse response. Biosystems Engineering, 88: 221-230.

Ehrentreich, F. 2002. Wavelet transform applications in analytical chemistry. Analytical and Bioanalytical Chemistry, 372: 115-121.

Haykin, S. 1994. Neural networks: a comprehensive foundation, Prentice Hall PTR.

Kalkan, H., Ince, N. F., Tewfik, A. H., Yardimci, Y. & Pearson, T. 2008. Classification of hazelnut kernels by using impact acoustic time-frequency patterns. EURASIP Journal on Advances in Signal Processing, 2008: 1-11.

Khalifa, S. & M. H. Komarizadeh. 2012. An intelligent approach based on adaptive neuro-fuzzy inference systems (ANFIS) for walnut sorting. Australian Journal of Crop Science, 6: 183-187.

Khalifa, S., Komarizadeh, M. H., Tousi, B. & Nikbakht, A. M. 2011. An intelligent system for grading walnuts based on acoustic emission and neural networks. Journal of Food, Agriculture & Environment, 9: 109-112.

Omid, M., Mahmoudi, A. & Omid, M. H. 2009. An intelligent system for sorting pistachio nut varieties. Expert Systems with Applications, 36: 11528-11535.

Onaran, I., Ince, N. F., Tewfik, A. H. & Cetin, A. E. 2007. A signal representation approach for discrimination between full and empty hazelnuts. EURASIP Journal on Advances in Signal Processing, 22: 2464-2468.

Pearson, T. 2001. Detection of pistachio nuts with closed shells using impact acoustics. Applied Engineering in Agriculture, 17: 249-253.

Send comment about this article

Name *

Enter Name.

Email Address *

Enter a valid email address.

Affiliation *

Enter a vaid affiliation.

Comments *

Enter comments (At leaset 10 words)

Security Code *