Estimation of the marbled score in live beef cattle based on ICA and US texture information
| Project/Area Number |
23500238
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Perception information processing/Intelligent robotics
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| Research Institution | National Institute of Advanced Industrial Science and Technology |
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Principal Investigator |
FUKUDA OSAMU 独立行政法人産業技術総合研究所, 生産計測技術研究センター, 主任研究員 (20357891)
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| Project Period (FY) |
2011 – 2013
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2013: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2012: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2011: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Keywords | 超音波 / パターン認識 / 畜産 / 独立成分分析 / 超音波画像 / テクスチャ |
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| Research Abstract |
To accurately estimate the Beef Marbling Standard(BMS) number of live cattle using ultrasound echo imagings, we have developed a image recognition method by use of a neural network. We examine the efficiency of applying Independent Component Analysis(ICA) to the compression of multidimensional image features. We have implemented the estimation tests by use of ultrasound echo imagings measured from live cattles. The estimation accuracy was evaluated based on the cross validation method. The results confirmed that the correlation coefficient between the actual and the estimated values was higher by ICA (R=0.70, p<0.01) than by PCA (R=0.62, p<0.01). Also, we conducted the comparison experiments between the ICA based estimation and the estimation by an experienced inspector. The both methods examined the same ultrasound images. As a result, we confirmed that the proposed method had much the same capability as the experienced inspector to estimate BMS number.
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Report
(4 results)
Research Products
(10 results)
