Beef Quality Identification Using Thresholding Method and Decision Tree Classification Based on Android Smartphone
Beef is one of the animal food products that have high nutrition because it contains carbohydrates, proteins, fats, vitamins, and minerals. Therefore, the quality of beef should be maintained so that consumers get good beef quality. Determination of beef quality is commonly conducted visually by com...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-01-01
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| Series: | Journal of Food Quality |
| Online Access: | http://dx.doi.org/10.1155/2017/1674718 |
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| _version_ | 1832558838785507328 |
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| author | Kusworo Adi Sri Pujiyanto Oky Dwi Nurhayati Adi Pamungkas |
| author_facet | Kusworo Adi Sri Pujiyanto Oky Dwi Nurhayati Adi Pamungkas |
| author_sort | Kusworo Adi |
| collection | DOAJ |
| description | Beef is one of the animal food products that have high nutrition because it contains carbohydrates, proteins, fats, vitamins, and minerals. Therefore, the quality of beef should be maintained so that consumers get good beef quality. Determination of beef quality is commonly conducted visually by comparing the actual beef and reference pictures of each beef class. This process presents weaknesses, as it is subjective in nature and takes a considerable amount of time. Therefore, an automated system based on image processing that is capable of determining beef quality is required. This research aims to develop an image segmentation method by processing digital images. The system designed consists of image acquisition processes with varied distance, resolution, and angle. Image segmentation is done to separate the images of fat and meat using the Otsu thresholding method. Classification was carried out using the decision tree algorithm and the best accuracies were obtained at 90% for training and 84% for testing. Once developed, this system is then embedded into the android programming. Results show that the image processing technique is capable of proper marbling score identification. |
| format | Article |
| id | doaj-art-0322bde596ef437db632fbeacb7be834 |
| institution | Kabale University |
| issn | 0146-9428 1745-4557 |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Food Quality |
| spelling | doaj-art-0322bde596ef437db632fbeacb7be8342025-02-03T01:31:25ZengWileyJournal of Food Quality0146-94281745-45572017-01-01201710.1155/2017/16747181674718Beef Quality Identification Using Thresholding Method and Decision Tree Classification Based on Android SmartphoneKusworo Adi0Sri Pujiyanto1Oky Dwi Nurhayati2Adi Pamungkas3Department of Physics, Diponegoro University, Semarang, IndonesiaDepartment of Biology, Diponegoro University, Semarang, IndonesiaDepartment of Computer System, Diponegoro University, Semarang, IndonesiaDepartment of Physics, Diponegoro University, Semarang, IndonesiaBeef is one of the animal food products that have high nutrition because it contains carbohydrates, proteins, fats, vitamins, and minerals. Therefore, the quality of beef should be maintained so that consumers get good beef quality. Determination of beef quality is commonly conducted visually by comparing the actual beef and reference pictures of each beef class. This process presents weaknesses, as it is subjective in nature and takes a considerable amount of time. Therefore, an automated system based on image processing that is capable of determining beef quality is required. This research aims to develop an image segmentation method by processing digital images. The system designed consists of image acquisition processes with varied distance, resolution, and angle. Image segmentation is done to separate the images of fat and meat using the Otsu thresholding method. Classification was carried out using the decision tree algorithm and the best accuracies were obtained at 90% for training and 84% for testing. Once developed, this system is then embedded into the android programming. Results show that the image processing technique is capable of proper marbling score identification.http://dx.doi.org/10.1155/2017/1674718 |
| spellingShingle | Kusworo Adi Sri Pujiyanto Oky Dwi Nurhayati Adi Pamungkas Beef Quality Identification Using Thresholding Method and Decision Tree Classification Based on Android Smartphone Journal of Food Quality |
| title | Beef Quality Identification Using Thresholding Method and Decision Tree Classification Based on Android Smartphone |
| title_full | Beef Quality Identification Using Thresholding Method and Decision Tree Classification Based on Android Smartphone |
| title_fullStr | Beef Quality Identification Using Thresholding Method and Decision Tree Classification Based on Android Smartphone |
| title_full_unstemmed | Beef Quality Identification Using Thresholding Method and Decision Tree Classification Based on Android Smartphone |
| title_short | Beef Quality Identification Using Thresholding Method and Decision Tree Classification Based on Android Smartphone |
| title_sort | beef quality identification using thresholding method and decision tree classification based on android smartphone |
| url | http://dx.doi.org/10.1155/2017/1674718 |
| work_keys_str_mv | AT kusworoadi beefqualityidentificationusingthresholdingmethodanddecisiontreeclassificationbasedonandroidsmartphone AT sripujiyanto beefqualityidentificationusingthresholdingmethodanddecisiontreeclassificationbasedonandroidsmartphone AT okydwinurhayati beefqualityidentificationusingthresholdingmethodanddecisiontreeclassificationbasedonandroidsmartphone AT adipamungkas beefqualityidentificationusingthresholdingmethodanddecisiontreeclassificationbasedonandroidsmartphone |