柑橘种子智能识别

Lau Bee Theng
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引用次数: 1

摘要

图像处理中的特征提取是一个日新月异的研究领域。[4]介绍了一种用于水果包装行业的柑橘MRI图像种子识别模型。为此,本研究提出了一种基于小波变换和活动区域识别的核磁共振图像种子识别模型。该方法将柑橘图像分割成圆形层和楔形,以确定对种子感兴趣的区域。这减少了查找水果是否含有种子的搜索空间(以像素为单位)。本文介绍了基于柑橘图像分割的种子识别的概念设计和研究成果。该改进可能适用于生物系统工程,用于区分有籽和无籽果实。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent citrus seed identification
Feature extraction in image processing is a research domain that changes rapidly. [4] introduces a model for identifying seeds from citrus MRI imagery for fruit packaging industry. Hence this research proposed a model for identifying seeds from MRI imagery preprocessed with wavelet transformation and active region identification. The proposed approach segments a citrus imagery into circular layers and wedges to identify the area of interest for seeds. This reduces searching space (in number of pixels) to find out whether a fruit contain seeds. This paper presents the conceptual design and findings from the research on seed identification from citrus imagery segmentation. The improvement might be suitable for bio systems engineering to differentiate fruits with and without seeds.
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