Segmentation Algorithm for Green Apples Recognition Based on K-means Algorithm

机译：基于K-means算法的青苹果识别分割算法

获取原文

获取原文并翻译 | 示例

页面导航

摘要
著录项
相似文献
相关主题

摘要

For the green apples that have similar green color with leaves, an apple recognition method based on K-means algorithm is proposed. The image is divided into 8*8 pixels blocks and the algorithm takes the block as Segmentation unit. Color difference R-G was selected as color feature and mean value, standard deviation and regional entropy of gray scale images are selected as texture features. The feature vectors which include color feature and texture features are extracted. Gap statistic was applied to calculate the best number of clusters. The algorithm is applied to 200 images that taken in different illumination conditions. The experiments results show that the apple fruits can be recognized successfully in front light conditions and back light conditions. The recognition rate reached 81%.

机译：针对与叶子颜色相似的绿色苹果，提出了一种基于K-means算法的苹果识别方法。图像被分为8 * 8像素块，算法以该块为分割单位。选择色差R-G作为颜色特征，选择灰度图像的平均值，标准偏差和区域熵作为纹理特征。提取包括颜色特征和纹理特征的特征向量。应用差距统计数据来计算最佳集群数。该算法适用于在不同照明条件下拍摄的200张图像。实验结果表明，在前照和逆光条件下，苹果果实都能被成功识别。识别率达到81％。

著录项

来源
《Proceedings of joint international agricultural conference (JIAC 2009)》|2009年|1-7|共7页
会议地点 Beijing(CN);Beijing(CN)
作者
Si Yongsheng; Liu Gang; Gao Rui;
展开▼
作者单位

Key Laboratory of MOE on Modern Precision Agriculture System Integration Research,China Agricultural University,Beijing 100083,China College of Information Science Technology,Agricultural University of Hebei,China;

Key Laboratory of MOE on Modern Precision Agriculture System Integration Research,China Agricultural University,Beijing 100083,China;

Key Laboratory of MOE on Modern Precision Agriculture System Integration Research,China Agricultural University,Beijing 100083,China;

展开▼
会议组织
原文格式 PDF
正文语种 eng
中图分类电子技术、计算机技术在农业上的应用;
关键词
Apple; Machine vision; Image recognition; K-means algorithm; Gap Statistic;

机译：苹果；机器视觉；图像识别； K-means算法；差距统计;

相似文献

外文文献
中文文献
专利

1. Recognition and localization of occluded apples using K-means clustering algorithm and convex hull theory: a comparison [J] . Wang Dandan, Song Huaibo, Tie Zhihui, Multimedia Tools and Applications . 2016,第6期

机译：基于K-means聚类算法和凸包理论的遮挡苹果识别与定位：比较
2. Recognition of green apples based on fuzzy set theory and manifold ranking algorithm [J] . Sun Sashuang, Wu Qian, Jiao Lin, Optik: Zeitschrift fur Licht- und Elektronenoptik: = Journal for Light-and Electronoptic . 2018,第期

机译：基于模糊集理论和歧管排名算法的绿苹果识别
3. Segmentation algorithm for the automatic recognition of Fuji apples at harvest [J] . Bulanon DM, Kataoka T, Ota Y, Biosystems Engineering . 2002,第4期

机译：富士苹果收获时自动识别的分割算法
4. Segmentation Algorithm for Green Apples Recognition Based on K-means Algorithm [C] . Si Yongsheng, Liu Gang, Gao Rui Joint international agricultural conference . 2009

机译：基于k均值算法的绿苹果识别分割算法
5. A K-means based watershed imaging segmentation algorithm for banana cluster quality inspection. [D] . Castillo Cepin, Gregorio Alfonso. 2016

机译：基于K均值的分水岭成像分割算法用于香蕉簇质量检测。
6. The Comparison of Clustering Algorithms K-Means and Fuzzy C-Means for Segmentation Retinal Blood Vessels [O] . Wiharto Wiharto, Esti Suryani 2020

机译：分割视网膜血管的聚类算法K均值和模糊C均值的比较
7. K-Means, Mean Shift, and SLIC Clustering Algorithms: A Comparison of Performance in Color-based Skin Segmentation [O] . Alorf Abdulkarim 2017

机译：K均值，均值漂移和SLIC聚类算法：基于颜色的皮肤分割性能的比较

Segmentation Algorithm for Green Apples Recognition Based on K-means Algorithm

摘要

著录项

相似文献

相关主题

期刊订阅