Abstract
Today agriculture field’s demands to develop such an intelligent system those provide accurate and timely information for an estimation of crop productivity. This paper designed an automated decision support system to estimate sunflower crop productivity information with interface between camera and computer software. The earlier steps of system generate overlapped flower yield information and latter steps count the seed from the flower head. Some beautiful flowers in the nature have Fibonacci relationship in their seeds pattern, i.e. sunflower, pineapple etc. The implementation parts based on two color model RGB and HSV. HSV provide better results for overlapped flower. The technique use image segmentation, morphological operation for overlapped flower count and edge detection for seed count.
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Rathore, H., Sharma, V.K., Chaturvedi, S., Sharma, K.D. (2019). Overlapped Sunflower Weighted Crop Yield Estimation Based on Edge Detection. In: Luhach, A., Singh, D., Hsiung, PA., Hawari, K., Lingras, P., Singh, P. (eds) Advanced Informatics for Computing Research. ICAICR 2018. Communications in Computer and Information Science, vol 955. Springer, Singapore. https://doi.org/10.1007/978-981-13-3140-4_2
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DOI: https://doi.org/10.1007/978-981-13-3140-4_2
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