[1]陈 钧,周井泉,程家文,等.水果分类的多模板匹配算法及其 FPGA 实现[J].计算机技术与发展,2023,33(04):34-39.[doi:10. 3969 / j. issn. 1673-629X. 2023. 04. 005]
　CHEN Jun,ZHOU Jing-quan,CHENG Jia-wen,et al.FPGA Implementation of Multi-template Matching Algorithm for Fruit Classification[J].,2023,33(04):34-39.[doi:10. 3969 / j. issn. 1673-629X. 2023. 04. 005]
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水果分类的多模板匹配算法及其 FPGA 实现()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
33
期数:
2023年04期
页码:
34-39
栏目:
嵌入式计算
出版日期:
2023-04-10

文章信息/Info

Title:
FPGA Implementation of Multi-template Matching Algorithm for Fruit Classification
文章编号:
1673-629X(2023)04-0034-06
作者:
陈 钧; 周井泉; 程家文; 谷文成
南京邮电大学 电子与光学工程学院、柔性电子学院,江苏 南京 210023
Author(s):
CHEN Jun; ZHOU Jing-quan; CHENG Jia-wen; GU Wen-cheng
School of Electronic and Optical Engineering,School of Flexible Electronics,NanjingUniversity of Posts and Telecommunications,Nanjing 210023,China
关键词:
实时; 识别与分类; 多模板匹配算法; 流水线; 稳定性
Keywords:
real-time; recognition and classification; multi-template matching algorithm; pipelining; stability
分类号:
TP391;TN911;TP332
DOI:
10. 3969 / j. issn. 1673-629X. 2023. 04. 005
摘要:
为了能够达到实时、高效,并且同时对多种水果进行识别与分类,设计了一种多模板匹配算法。 该算法的设计主要包括了形状特征提取、特征与模板数据库的匹配、识别与分类。 特征提取的过程包括了图像处理的灰度化、均值滤波、Sobel 边缘检测、梯度统计、归一化等一系列模块。 以水果的形状特征来构建一个多模板数据库,将所需识别的水果与模板数据库进行匹配与分类。 以紫光同创的 PGL22G-6MBG324 产品搭建的实时图像处理平台,利用现场可编程逻辑门阵列(field programmable gate array,FPGA) 的流水线以及并行处理结构的优点,实现了多模板匹配算法。对 FPGA 实现的算法选取了芒果、香蕉、苹果、猕猴桃四种水果进行了测试。识别与分类的时间在 12.10 ms 内,在固定位置的识别准确率可达98% 以上。 与一些神经网络的算法进行对比,具有较高的实时性。 并且测试了该算法受光照、平移、缩放、微旋的影响较小。 结果表明该算法具有实时性、有效性、稳定性。
Abstract:
In order to achieve real - time and efficient recognition and classification of a variety of fruits, a multi - template matchingalgorithm is designed. The design of the algorithm mainly includes shape feature extraction,feature matching with template database,recognition and classification. The process of feature extraction includes a series of modules of image processing such as gray-scale,meanfiltering,Sobel edge detection,gradient statistics, normalization and so on. A multi-template database is constructed based on the shapefeature of fruits,and the fruits to be recognized are matched and classified with the template database. Based on the real-time image processing platform of PGL22G-6MBG324 created by Unigroup,the multi-template matching algorithm is realized by using the pipeline offield programmable gate array ( FPGA) and the advantages of parallel processing structure. Mango, banana, apple and kiwifruit areselected for the test of algorithm implemented by FPGA. The recognition and classification time is within 12. 10 ms,and the recognitionaccuracy can reach more than 98% at fixed positions. Compared with some neural network algorithms, it has higher real - timeperformance and is less affected by illumination,translation,scaling and micro-rotation. The results show that the proposed algorithm isreal-time,effective and stable.

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更新日期/Last Update: 2023-04-10