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Identifikasi Barcode pada Gambar yang Ditangkap Kamera Digital Menggunakan Metode JST

机译:基于ANN方法的数码相机拍摄图像的条形码识别

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— Barcode, Learning Vector Quantization, Jaringan Syaraf Tiruan ? Abstrak In today’s modern society, almost every consumer product has a barcode label. But the barcode reader with laser type has the disadvantage of not being able to recognize the barcode has a scratch or noise. However, other techniques have been developed by using a digital camera for barcode identification. ANN has been widely used for identification of various patterns. Barcode identification process consists of the ANN training process and the identification process. Training process using the LVQ (Learning Vector Quantization). Identification process consists of several stages: image acquisition, preprocessing, locating barcode, testing and verification process. Based on test results LVQ method can be used for photo identification barcode with good performance. The test results showed an accuracy of 73.6% rate of 72 images were tested with an average time is 0.5 seconds. While the time required to find the location of the barcode is about 6 seconds using a block size of 32x32 pixels. ? Keyword — Barcode, Learning Vector Quantization, Artificial Neural Network.
机译:—条形码,学习矢量量化,Jaringan Syaraf Tiruan? Abstrak在当今的现代社会中,几乎所有消费品都带有条形码标签。但是,激光类型的条形码阅读器的缺点是无法识别条形码是否有刮擦或噪音。但是,通过使用数字照相机进行条形码识别已经开发了其他技术。人工神经网络已被广泛用于各种模式的识别。条形码识别过程包括ANN训练过程和识别过程。使用LVQ(学习矢量量化)进行培训。识别过程包括几个阶段:图像获取,预处理,条形码定位,测试和验证过程。根据测试结果,LVQ方法可用于具有良好性能的照片识别条形码。测试结果表明,对72幅图像的准确率达到了73.6%,平均时间为0.5秒。使用32x32像素的块大小查找条形码位置所需的时间约为6秒。 ?关键字—条形码,学习向量量化,人工神经网络。

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