Araştırma Makalesi
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Yıl 2019, Cilt: 1 Sayı: 2, 71 - 83, 16.12.2019

Öz

Kaynakça

  • [1] SAGLIK, from <https://www.saglik.gov.tr/TR,55310/mantar-zehirlenmeleri-uzerine-yapilan-basin-aciklamasi-14052019.html/>, last accessed july 21, 2019.
  • [2] Neuman M.R, Sapirstein H.D, Shwedyk E, Bushuk W., (1989 a). Wheat grain colour analysis by digital image processing I.methodology. Journal of Cereal Science, 10(3), 175-182. DOI:10.1016/S0733-5210(89)80046-3.
  • [3] Neuman M.R., Sapirstein H.D., Shwedyk E. and Bushuk W., (1989 b). Wheat grain colour analysis by digital image processing II.wheat class discrimination. Journal of Cereal Science, 10(3), 183-188. DOI:10.1016/S0733-5210(89)80047-5.
  • [4] Göknur-Dursun, İ., 2001. Bazı Taneli Ürünlerin İzdüşüm Alanlarının Görüntü İşlemeyle Belirlenmesi. Tarım Bilimleri Dergisi, 7(3), 102- 107. DOI: 10.1501/Tarimbil_0000000661.
  • [5] Njoroge, J.B., Ninomiya, K., Kondo, N., Toita, H., 2002. Automated Fruit Grading System Using Image Processing. SICE 2002, Proceedings of the 41st SICE Annual Conference, 1346-1351. DOI:10.1109/SICE.2002.1195388.
  • [6] Feng, G., Qixin, C., 2004. Study on Color Image Processing Based Intelligent Fruit Sorting System. Proceedings of the 5th World Congress on Intelligent Control and Automation, 6, 4802-4805. DOI: 10.1109/WCICA.2004.1343622.
  • [7] Chamelat, R., Rosso, E., Choksuriwong, A., Rosenberger, C., Laurent, H., Bro, P., 2006. Grape detection by image processing. ECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics, 7-10 November. DOI: 10.1109/IECON.2006.347704.
  • [8] Lino, A.C.L. ,Sanches, J., Dal Fabbro, I.M., 2008. Image Processing Techniques For Lemons and Tomatoes Classification. Bragantia, Campinas, v.67, n.3, p.785-789. DOI:10.1590/S0006-87052008000300029
  • [9] Tonguç, G., Yakut, A.K., 2009. Fruit Grading Using Digital Image Processing Techniques. Tarım Makinaları Bilimi Dergisi, 5(1), 93–101.
  • [10] Omid , M., Khojastehnazhand, M., Tabatabaeefar, A., 2010. Estimating Volume And Mass Of Citrus FruitsBy Image Processing Technique. Journal of Food Engineering,100, 315–321. DOI: 10.1016/j.jfoodeng.2010.04.015.
  • [11] Al-Mallahi,A., Kataoka,T., Okamoto,H., Shibata,Y., 2010. An image processing algorithm for detecting in-line potato tubers without singulation. Computers and Electronics in Agriculture, 70, 239–244. DOI: 10.1016/j.compag.2009.11.001.
  • [12] Liming, X., Yanchao Z., 2010. Automated strawberry grading system based on image processing. Computers and Electronics in Agriculture, 71S, S32–S39. DOI: 10.1016/j.compag.2009.09.013.
  • [13] Aggelopoulou, A.D., Bochtis, D., Fountas, S., Swain, K.C., Gemtos, T.A., Nanos, G.D., 2011. Yield prediction in apple orchards based on image processing. Precision Agriculture, 12(3), 448-456. DOI: 10.1007/s11119-010-9187-0.
  • [14] Gastélum-Barrios, A., Bórquez-López, R. A., Rico-García, E., Toledano-Ayala, M., Soto-Zarazúa, G. M. , 2011. Tomato quality evaluation with image processing: A review. African Journal of Agricultural Research Vol. 6(14), pp. 3333-3339. DOI: 10.5897/AJAR11.108.
  • [15] Balestani, A.M., Moghaddam, P. A., Motlaq, A.M., Dolaty, H., 2012. Sorting and Grading of Cherries on the Basis of Ripeness, Size and Defects by Using Image Processing Techniques. International Journal of Agriculture and Crop Sciences, 4-16,1144-1149. ISSN:2227-670X.
  • [16] Sofu, M.M., Er, O., Kayacan, M.C., B. Cetişli, 2013. Elmaların Görüntü İşleme Yöntemi ile Sınıflandırılması ve Leke Tespiti. Gıda Teknolojileri Elektronik Dergisi, 8 (1), 12- 25. e-ISSN:1306-7648.
  • [17] Font, D., Tresanchez, M., Pallejà, T., Teixidó, M., Martinez, D., Moreno, J., Palacín , J., 2014. An image processing method for in-line nectarine variety verification based on the comparison of skin feature histogram vectors. Computers and Electronics in Agriculture, 102, 112–119. DOI: 10.1016/j.compag.2014.01.013.
  • [18] Bhange, M., Hingoliwala, H.A., 2015. Smart Farming: Pomegranate Disease Detection Using Image Processing. Procedia Computer Science, 58, 280 – 288. DOI: 10.1016/j.procs.2015.08.022.
  • [19] Beyer, K., Goldstein, J., Ramakrishnan, R., Shaft U., 1998. When Is “Nearest Neighbor” Meaningful?. ICDT’99, LNCS 1540, 217-235.
  • [20] Khan, M., Ding, Q., Perrizo, W., 2002. K-Nearest Neighbor Classification on Spatial Data Streams Using P-Trees. PAKDD 2002, 6th Pacific-Asia Conference, 517-518. DOI: 10.1007/3-540-47887-6.
  • [21] Silahtaroğlu, G., (2016). Veri Madenciliği. Papatya Bilim, pages 118-119, 97-98.
  • [22] Özkan, Y., (2016). Veri Madenciliği Yöntemleri. Papatya Bilim, 143.
  • [23] Gendrin, C., (2008). Chemical imaging and chemometrics for the analysis of pharmaceutical solid dosage forms. Engineering Sciences, Universit´e Louis Pasteur – Strasbourg I.

MUSHROOM SPECIES DETECTION USING IMAGE PROCESSING TECHNIQUES

Yıl 2019, Cilt: 1 Sayı: 2, 71 - 83, 16.12.2019

Öz

There are many kinds of mushrooms in the world,
some of them are edible and some are poisonous. People may want to eat the
mushrooms they encounter in nature, as a result of which they may become
poisoned or even die. In this research image processing techniques, K-NN and
Naive Bayes algorithms were used to classify mushroom species in Selçuk
University Campus. As a result of the research, K-NN algorithm achieved 80% and
Naive Bayes algorithm achieved 96% accuracy.

Kaynakça

  • [1] SAGLIK, from <https://www.saglik.gov.tr/TR,55310/mantar-zehirlenmeleri-uzerine-yapilan-basin-aciklamasi-14052019.html/>, last accessed july 21, 2019.
  • [2] Neuman M.R, Sapirstein H.D, Shwedyk E, Bushuk W., (1989 a). Wheat grain colour analysis by digital image processing I.methodology. Journal of Cereal Science, 10(3), 175-182. DOI:10.1016/S0733-5210(89)80046-3.
  • [3] Neuman M.R., Sapirstein H.D., Shwedyk E. and Bushuk W., (1989 b). Wheat grain colour analysis by digital image processing II.wheat class discrimination. Journal of Cereal Science, 10(3), 183-188. DOI:10.1016/S0733-5210(89)80047-5.
  • [4] Göknur-Dursun, İ., 2001. Bazı Taneli Ürünlerin İzdüşüm Alanlarının Görüntü İşlemeyle Belirlenmesi. Tarım Bilimleri Dergisi, 7(3), 102- 107. DOI: 10.1501/Tarimbil_0000000661.
  • [5] Njoroge, J.B., Ninomiya, K., Kondo, N., Toita, H., 2002. Automated Fruit Grading System Using Image Processing. SICE 2002, Proceedings of the 41st SICE Annual Conference, 1346-1351. DOI:10.1109/SICE.2002.1195388.
  • [6] Feng, G., Qixin, C., 2004. Study on Color Image Processing Based Intelligent Fruit Sorting System. Proceedings of the 5th World Congress on Intelligent Control and Automation, 6, 4802-4805. DOI: 10.1109/WCICA.2004.1343622.
  • [7] Chamelat, R., Rosso, E., Choksuriwong, A., Rosenberger, C., Laurent, H., Bro, P., 2006. Grape detection by image processing. ECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics, 7-10 November. DOI: 10.1109/IECON.2006.347704.
  • [8] Lino, A.C.L. ,Sanches, J., Dal Fabbro, I.M., 2008. Image Processing Techniques For Lemons and Tomatoes Classification. Bragantia, Campinas, v.67, n.3, p.785-789. DOI:10.1590/S0006-87052008000300029
  • [9] Tonguç, G., Yakut, A.K., 2009. Fruit Grading Using Digital Image Processing Techniques. Tarım Makinaları Bilimi Dergisi, 5(1), 93–101.
  • [10] Omid , M., Khojastehnazhand, M., Tabatabaeefar, A., 2010. Estimating Volume And Mass Of Citrus FruitsBy Image Processing Technique. Journal of Food Engineering,100, 315–321. DOI: 10.1016/j.jfoodeng.2010.04.015.
  • [11] Al-Mallahi,A., Kataoka,T., Okamoto,H., Shibata,Y., 2010. An image processing algorithm for detecting in-line potato tubers without singulation. Computers and Electronics in Agriculture, 70, 239–244. DOI: 10.1016/j.compag.2009.11.001.
  • [12] Liming, X., Yanchao Z., 2010. Automated strawberry grading system based on image processing. Computers and Electronics in Agriculture, 71S, S32–S39. DOI: 10.1016/j.compag.2009.09.013.
  • [13] Aggelopoulou, A.D., Bochtis, D., Fountas, S., Swain, K.C., Gemtos, T.A., Nanos, G.D., 2011. Yield prediction in apple orchards based on image processing. Precision Agriculture, 12(3), 448-456. DOI: 10.1007/s11119-010-9187-0.
  • [14] Gastélum-Barrios, A., Bórquez-López, R. A., Rico-García, E., Toledano-Ayala, M., Soto-Zarazúa, G. M. , 2011. Tomato quality evaluation with image processing: A review. African Journal of Agricultural Research Vol. 6(14), pp. 3333-3339. DOI: 10.5897/AJAR11.108.
  • [15] Balestani, A.M., Moghaddam, P. A., Motlaq, A.M., Dolaty, H., 2012. Sorting and Grading of Cherries on the Basis of Ripeness, Size and Defects by Using Image Processing Techniques. International Journal of Agriculture and Crop Sciences, 4-16,1144-1149. ISSN:2227-670X.
  • [16] Sofu, M.M., Er, O., Kayacan, M.C., B. Cetişli, 2013. Elmaların Görüntü İşleme Yöntemi ile Sınıflandırılması ve Leke Tespiti. Gıda Teknolojileri Elektronik Dergisi, 8 (1), 12- 25. e-ISSN:1306-7648.
  • [17] Font, D., Tresanchez, M., Pallejà, T., Teixidó, M., Martinez, D., Moreno, J., Palacín , J., 2014. An image processing method for in-line nectarine variety verification based on the comparison of skin feature histogram vectors. Computers and Electronics in Agriculture, 102, 112–119. DOI: 10.1016/j.compag.2014.01.013.
  • [18] Bhange, M., Hingoliwala, H.A., 2015. Smart Farming: Pomegranate Disease Detection Using Image Processing. Procedia Computer Science, 58, 280 – 288. DOI: 10.1016/j.procs.2015.08.022.
  • [19] Beyer, K., Goldstein, J., Ramakrishnan, R., Shaft U., 1998. When Is “Nearest Neighbor” Meaningful?. ICDT’99, LNCS 1540, 217-235.
  • [20] Khan, M., Ding, Q., Perrizo, W., 2002. K-Nearest Neighbor Classification on Spatial Data Streams Using P-Trees. PAKDD 2002, 6th Pacific-Asia Conference, 517-518. DOI: 10.1007/3-540-47887-6.
  • [21] Silahtaroğlu, G., (2016). Veri Madenciliği. Papatya Bilim, pages 118-119, 97-98.
  • [22] Özkan, Y., (2016). Veri Madenciliği Yöntemleri. Papatya Bilim, 143.
  • [23] Gendrin, C., (2008). Chemical imaging and chemometrics for the analysis of pharmaceutical solid dosage forms. Engineering Sciences, Universit´e Louis Pasteur – Strasbourg I.
Toplam 23 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Research Articles
Yazarlar

Yasemin Rukiye Erkan 0000-0002-6843-3289

Humar Kahramanlı Örnek Bu kişi benim 0000-0003-2336-7924

Yayımlanma Tarihi 16 Aralık 2019
Kabul Tarihi 30 Temmuz 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 1 Sayı: 2

Kaynak Göster

APA Erkan, Y. R., & Kahramanlı Örnek, H. (2019). MUSHROOM SPECIES DETECTION USING IMAGE PROCESSING TECHNIQUES. International Journal of Engineering and Innovative Research, 1(2), 71-83.

Open Journal Systems (BOAI)

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