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:: Volume 5, Issue 1 (Spring 2020) ::
FOP 2020, 5(1): 51-60 Back to browse issues page
Automated flower enumeration, a felicitous method developed for the floriculture industries
Sonam Bahuguna, Shubham Anchal, Anjali Chandel, Mamta Devi, Bhavya Bhargava, Amit Kumar
CSIR-Institute of Himalayan Bioresource Technology
Abstract:   (40 Views)
Floriculture has become one of the vital profitable businesses in Indian agriculture. The important flowers which are internationally traded include lilium, tagetes, rose, tulip, chrysanthemum, carnation, tuberose, crossandra, etc. Estimation of yield at the time of harvesting of flowers is an important aspect in these floriculture businesses which help strategize their marketing. The present study thus focuses on Lilium and Tagetes (marigold), which are well-known cut and loose flowers, respectively. Cut flowers are harvested when buds start showing color while loose flowers are harvested depending upon the varieties when it attains full size. Conventionally, yield estimations are done manually by counting buds and flowers, which is often erroneous and time-consuming. This paper attempts to develop an automated system for counting Lilium buds and Tagetes flowers at the time of its harvesting using digital image processing techniques. The process implicates image acquisition, pre-processing, thresholding, watershed and finally buds/flower counting for yield estimation. The validation of the results has been done by comparing the results obtained through the manual method as well as by automated counting. The entire process was repeated four times with four different photos to judge the robustness of the techniques. The obtained result was 95.61% accurate for Lilium and 96.66% in the case of Tagetes, airing the possibilities of using the approach. The systematic workflow with pros and cons has been discussed in this paper.
Keywords: Floriculture, Counting, Digital Image Processing, Thresholding, Yield estimation.
Full-Text [PDF 472 kb]   (16 Downloads)    
Type of Study: Research | Subject: General
Received: 2020/11/17 | Accepted: 2021/10/11 | Published: 2021/10/11
References
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25. Bairwa, N., Agrawal, K.N. (2014). Counting of flowers using image processing, International Journal of Computer Applications, 3, 0975-8887.
26. Bindu, S., Prudhvi, S., Hemalatha, G., Sekhar, M. N. Nanchariahl, M.V. (2014) .Object detection from complex background image using circular hough transform. International Journal of Engineering Research and Applications, 4, 23-28.
27. Biradar, B.V., Shrikhande, S.P. (2015). Flower detection and counting using morphological and segmentation technique. International Journal of Computer Science Information Technology, 6, 2498-2501.
28. Dixit, P., Tripathi, S., Verma, K.N. (2013). A brief study on marigold (Tagetes species). International Research Journal of Pharmacy, 4, 43-48.
29. Dorj, O.U., Lee, K.K., Lee, M. (2013). A computer vision algorithm for tangerine yield estimation. International Journal of Bio-Science and Bio-Technology, 5, 101-110. [DOI:10.14257/ijbsbt.2013.5.5.11]
30. Floristry and Floriculture Industry Statistics. (2019). https://www.petalrepublic.com/floristry-and-floriculture-statistics/.
31. Gowsalya, K., Sridevi, P. (2019). Prediction of fruits and flowers using image analysis techniques. International Research Journal of Engineering and Technology, 6, 1202-1208.
32. Lim, K. B., Hwang, Y.J., Younis, A. (2014). Classical vs. modern genetic and breeding approaches for Lily (Lilium) crop improvement. Flower Research Journal, 22, 39-47. [DOI:10.11623/frj.2014.22.2.1]
33. Mukherjee, D. (2008). Speciality Cut Flowers Production Technologies. Bidhan Sarani, Kolkata, India.
34. Nisar, H., Yang, Z.H., Ho, K.Y. (2015). Predicting yield of fruit and flowers using digital image analysis. Indian Journal of Science and Technology, 8, 0974-5645. [DOI:10.17485/ijst/2015/v8i32/93730]
35. Observatory of Economic Complexity. 2019. https://oec.world/en/profile/hs92/cutflowers?redirect=true#:~:text=In%202019%2C%20Cut%20Flowers%20were,0.049%25%20of%20total%20world%20trade. [DOI:10.29226/TR1001.2018.59]
36. Sarkate, S.R., Kalyankar, V.N. Khanale, B.P. (2013). Application of computer vision and color image segmentation for yield prediction precision. International Conference on Information Systems and Computer Networks (IEEE), 9-13. [DOI:10.1109/ICISCON.2013.6524164]
37. Schneider, A.C., Rasband, S.W. Eliceiri, W.K. (2012). NIH Image to ImageJ: 25 years of image analysis. Nature America, 9, 671-675. [DOI:10.1038/nmeth.2089]
38. Scott, B.J., Gent, H.D., Hay, S.F., Pethybridge, J.S. (2015). Estimation of Pyrethrum flower number using digital imagery. American Society for Horticultural Science, 25, 1943-7714. [DOI:10.21273/HORTTECH.25.5.617]
39. Sethy, P.K., Routray, B., Behera, S.K. (2019). Detection and counting of marigold flower using image processing technique. In: Advances in Computer Communication and Control. Springer, Singapore. 87-93. [DOI:10.1007/978-981-13-3122-0_9]
40. Sundar, S.V. Bagyamani, J. (2015). Flower counting in yield approximation using digital image processing techniques. International Journal of Advance Research in Science and Engineering, 4, 2319-8354.
41. Sural, S., Qian, G., Pramanik, S. (2002). Segmentation and histogram generation using the HSV color space for image retrieval. International Conference on Image Processing, II-589-II-592. [DOI:10.1109/ICIP.2002.1040019]
42. Syal, A., Garg, D., Sharma, S. (2013)., A survey of computer vision methods for counting fruits and yield prediction. International Journal of Computer Science Engineering, 2, 2319-7323.
43. Thangam, M., Safeena, A.S., Devi, P.S., Singh, P.N. (2016). Lilium cut flower production under naturally ventilated polyhouse, Central Coastal Agricultural Research Institute, Indian Council of Agricultural Research, Goa, India.
44. Hoo, Z.Y. (2015). Automated fruit and flower counting using digital image analysis (Doctoral Dissertation, UTAR).
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Bahuguna S, Anchal S, Chandel A, Devi M, Bhargava B, Kumar A. Automated flower enumeration, a felicitous method developed for the floriculture industries. FOP. 2020; 5 (1) :51-60
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