Elaeis Guineensis leaf image segmentation: A comparative study and analysis

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外文摘要：The main intention of the research is to identify and segment the diseased-pattern section that comprised of colour and texture， apart from the background which is also known as region of interest (ROI)。 Hence， a comparative study related to segmentation of Elaeis Guineensis (oil palm) leaf images extracted from the oil palm will be evaluated and validated。 The database consists of images of leaf suffering from nutrition deficiency namely nitrogen， potassium and magnesium。 Three different techniques of segmentation are investigated specifically the Otsu global threshold， local threshold and global threshold with tophat。 Next， the segmentation algorithms have been developed to be capable to perform segmentation process using the leaf images that were exposed to varying illumination。 Initial findings showed that Otsu global threshold is the best segmentation based on the tested images。

外文关键词：

Otsu methodROISegmentationimage processingnutrition deficiencyoil palm leafthreshold

作者：

Hairuddin, Muhammad Asraf、Tahir, Nooritawati Md、Baki, Shah Rizam Shah、Ashar, Nur Dalila Khirul

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作者单位：

Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia|c|

会议名称：

IEEE International Conference on System Engineering and Technology

会议地点：

Shah Alam(MY)

会议母体文献：

2013 IEEE 3rd International Conference on System Engineering and Technology

页码：

248-251

出版时间：

2013

DOI：

10.1109/ICSEngT.2013.6650179