WO2011145287A1 - 穀粒外観品位判別装置における品位別重量比率の算出方法 - Google Patents
穀粒外観品位判別装置における品位別重量比率の算出方法 Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/66—Trinkets, e.g. shirt buttons or jewellery items
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N2021/8466—Investigation of vegetal material, e.g. leaves, plants, fruits
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/85—Investigating moving fluids or granular solids
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/243—Classification techniques relating to the number of classes
- G06F18/2431—Multiple classes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30128—Food products
Definitions
- the present invention relates to a method for calculating the weight ratio of grains such as rice, wheat, beans, and corn according to grade in a grain appearance quality discrimination device.
- each of the deflated grains is sorted into sized grains and scrap grains, or sized grains and torn grains, immature grains, dead rice, colored grains, torn grains It is necessary to sort into other damaged grains and to measure the selected grains, which takes time and labor.
- the grain appearance quality discriminating apparatus for example, images about 1000 sample grains at once using a scanner and discriminates the quality of each sample grain using image information obtained by the imaging. It is an apparatus that can easily evaluate the quality of grains (see Patent Documents 1 and 2).
- FIG. 6 shows a conventional flow for calculating the grain-by-grade weight ratio using the grain appearance quality discrimination device described in Patent Document 1.
- Imaging processing S11
- the grain appearance quality discriminating apparatus captures an image of a sample grain of the grain to be evaluated, and acquires imaging data of the sample grain.
- Data processing S12
- the grain appearance quality discriminating apparatus extracts data related to the quality of the sample grain based on the imaging data.
- Quality discrimination processing S13
- the grain appearance quality discriminating apparatus discriminates the quality of the sample grain by comparing data related to the quality of the sample grain with a preset threshold value.
- Grain count processing S14
- the grain appearance quality discriminating device counts the number of grains for each grade of the sample grain whose grade is discriminated.
- the grain appearance quality discriminating device calculates the weight ratio for each grade based on the number of sample grains counted for each grade and the weight conversion coefficient (one grain weight) per grain set in advance for each grade.
- Output process The grain appearance quality discriminating apparatus outputs a calculated value of the weight ratio by quality of the sample grain to a printer or a monitor.
- FIG. 7 shows an example of calculating the weight ratio of brown rice by grade according to the conventional method.
- the quality of the brown rice is shown as “discrimination category”.
- the weight conversion coefficient (one grain weight) per grain of brown rice is set in advance for each discrimination category (quality).
- the grain appearance quality discriminating apparatus obtains a converted weight by multiplying the number of sample grains aggregated according to the discrimination category (quality) by the weight conversion factor (one grain weight), and the total weight of the converted weights. Is calculated as a weight ratio for each distinction category (quality).
- the weight ratio by grain quality can be calculated easily and quickly.
- FIG. 8 shows a comparative example of two crushed particles.
- the crushed particles shown in FIG. 8 (a) and the crushed particles shown in FIG. 8 (b) are clearly different in size.
- the method using the conventional grain appearance quality discriminating apparatus described above treats both as one crushed grain and multiplies the same weight conversion factor (one grain weight) to obtain a converted weight, which is not necessarily accurate. The weight ratio cannot be calculated well.
- the present invention provides a method that can accurately calculate the weight ratio of grains such as rice, wheat, beans, corn, etc., by using the grain appearance quality discrimination device.
- the purpose is to provide.
- the present invention provides a method for calculating a weight ratio by grade in a grain appearance quality discriminating apparatus that images a grain by an imaging unit and discriminates the quality of the grain based on the imaging data.
- the number of pixels in the imaging data of the plurality of grains whose grades have been discriminated, and by the grade By multiplying the total number of pixels by a weight conversion coefficient per pixel that is set in advance for each grade, the number of pixels is converted to a weight for each grade, and based on the weight for each grade, The weight ratio is calculated.
- the imaging means for imaging the grain is an image reading apparatus.
- the method for calculating the weight ratio by grade in the grain appearance quality discriminating apparatus of the present invention is to count the number of pixels in the image data of the grain by grade and set one pixel that is preset for each grade by the number of pixels counted by the grade.
- the number of pixels is converted to weight by grade by multiplying the weight conversion factor per unit, and the weight ratio by grade is calculated based on the weight by grade. Therefore, the weight ratio by grain quality can be calculated more accurately than in the past.
- the method for calculating the weight ratio by grade in the grain appearance quality discriminating apparatus of the present invention is capable of imaging a plurality of grains at a time if the imaging means for imaging the grains is an image reading apparatus, and therefore, by grain grade.
- the weight ratio can be calculated easily and quickly.
- the external view which shows an example of the grain appearance quality discrimination
- size differs.
- size differs.
- FIG. 1 shows an example of a grain appearance quality discrimination device used in the method of the present invention.
- the grain appearance quality discriminating apparatus 1 includes an imaging means 2 for imaging grains such as rice, wheat, beans, and corn, and a quality discriminating means 4 connected to the imaging means 2 by a cable 3.
- an imaging means 2 for imaging grains such as rice, wheat, beans, and corn
- a quality discriminating means 4 connected to the imaging means 2 by a cable 3.
- a commercially available scanner can be used for the imaging means 2.
- a personal computer can be used for the quality discriminating means 4.
- the imaging means 2 includes a main body 2a, an imaging base 2b provided on the upper surface of the main body 2a, and a cover 2c for opening and closing the upper surface of the imaging base 2b.
- the main body 2a includes a light source composed of a white fluorescent lamp or a white LED that irradiates the grain placed on the imaging stand 2b, a color CCD line sensor that receives reflected light from the grain, and the like.
- the light-receiving part which consists of is provided.
- the grain G is accommodated in an aligned manner on the imaging tray 5 and placed on the imaging stand 2b.
- the quality discriminating means 4 performs image processing on the image data of the grain imaged by the imaging means 2 and extracts optical information such as the color of the grain and shape information such as the outer shape, and the like.
- a threshold for determining the quality of the grain compared with the information extracted in the image processing unit, and a weight conversion coefficient per pixel for calculating a weight ratio by quality of the grain A calculation unit that stores and sets the dot weight in advance, and a display that displays a result obtained by the calculation control unit.
- the grain appearance quality discriminating apparatus 1 used in the method of the present invention sends an image signal of a plurality of grains acquired by the imaging means 2 to the quality discriminating means 4, and the grain discriminating means 4 uses each grain. Grain quality is discriminated and the weight ratio of the grain by grade is calculated.
- the grain appearance quality discrimination device used in the method of the present invention images at least grains of rice, wheat, beans, corn, etc., and discriminates the grain quality based on the imaging data.
- the present invention is not limited to one provided with imaging means such as a scanner that images the plurality of grains at a time.
- the grain appearance quality discriminating apparatus used in the method of the present invention may be one that images grains one by one, such as a grain quality discriminating apparatus described in Japanese Patent Application Laid-Open No. 2008-298695.
- FIG. 2 shows a flow of the present invention for calculating the weight ratio of brown rice by quality using the grain appearance quality discrimination device 1.
- the method of the present invention is started by placing an imaging tray 5 containing a plurality of brown rice sample grains on the imaging stand 2 b of the imaging means 2.
- Imaging process (S1) First, the grain appearance quality discriminating apparatus 1 images a plurality of sample grains stored in the imaging tray 5 by the imaging means 2 and acquires imaging data of the sample grains.
- S2 Data processing
- the grain appearance quality discriminating apparatus 1 sends the acquired imaging data to the quality discriminating means 4 and relates to the quality of the sample grain such as the outer shape, area, length, width, color, and body ratio by image processing. Information to be extracted.
- the grain appearance quality discriminating apparatus 1 discriminates the quality of each sample grain by comparing the information related to the quality with a preset threshold value in the quality discriminating means 4.
- Pixel count processing The grain appearance quality discriminating apparatus 1 aggregates the number of pixels of the sample grain by grade based on the outer shape in the grade discriminating means 4 for the sample grain whose grade has been discriminated.
- Weight ratio calculation process S5 The grain appearance quality discriminating apparatus 1 then sorts by quality based on the number of pixels of the sample grains that are aggregated by quality in the quality discrimination means 4 and the weight conversion coefficient (dot weight) per pixel that is preset for each quality. The weight ratio is calculated.
- the grain appearance quality discriminating apparatus 1 outputs the calculated value of the weight ratio by quality of the sample grain to the display.
- the grain appearance quality discriminating apparatus 1 finishes the grade discrimination for all the sample grains, counts the number of pixels by grade for all the sample grains, and the weight ratio by grade for all the sample grains It ends at the stage of calculating.
- said each process with respect to a some brown rice may be performed in parallel, and may be performed collectively.
- FIG. 3 shows a diagram comparing the two crushed particles shown in FIG. 8 at the pixel level.
- FIG. 3A shows 569 pixels
- FIG. 3B shows 74 pixels, which shows that the size is about three times different. According to the method of the present invention, it is possible to calculate the weight ratio of brown rice classified into the same quality as described above in consideration of the size difference.
- FIG. 4 shows a calculation example of the weight ratio of brown rice by grade according to the method of the present invention.
- the quality of the brown rice is shown as “discrimination category”.
- a weight conversion coefficient (dot weight) per brown rice pixel is stored and set in advance for each discrimination category (quality).
- the grain appearance quality discriminating apparatus 1 obtains the converted weight by multiplying the number of dots (number of pixels) of the sample grain totaled for each discrimination category (quality) by the weight conversion coefficient (dot weight), and the conversion The ratio of the weight to the total weight is calculated as a weight ratio for each discrimination category (quality).
- the “weight conversion coefficient (number of dots)” in FIG. 4 is rounded off, the calculated value of “converted weight” is slightly different from the actual value.
- the weight conversion coefficient (dot weight) per pixel of brown rice shown in FIG. 4 indicates the actual weight of brown rice classified according to quality and the dots of brown rice classified according to the quality counted by the grain appearance quality discrimination device. It can be obtained in advance by using the number (number of pixels). If the weight conversion factor is determined by the production area, variety, or combination of production area and variety of brown rice, the weight ratio by quality can be calculated more accurately in the method of the present invention.
- FIG. 5 shows another calculation example of the grain-by-grade weight ratio according to the method of the present invention.
- the quality of the brown rice is shown as “discrimination category”.
- brown rice is used as the grain, but according to the method of the present invention, the weight ratio of other grains such as white rice can be calculated with high accuracy.
- one evaluation category of brown rice in Japan is used as the discrimination category (quality).
- other evaluation categories particularly evaluation categories of China and other countries, are used.
- the weight ratio by grain quality can be calculated with high accuracy.
- the quality conversion means 4 of the grain appearance quality discriminating apparatus 1 uses the various threshold values for discriminating the quality of the evaluation category and the weight conversion coefficient per pixel of the grain calculated corresponding to each grade. Needless to say, (dot weight) may be set in advance.
- the weight conversion factor (dot weight) per pixel of the grain takes into account the size of the grain, but if the size of the grain includes thickness information. It is preferable to accurately calculate the weight ratio by quality.
- the weight conversion coefficient (dot weight) per pixel of the grain takes into account the size of the grain, but may further take into account the color information of the grain. If the weight conversion count (dot weight) per grain pixel takes into account the color information of the grain, the weight ratio by quality can be calculated with higher accuracy.
- Each calculation example of the grain-by-grade weight ratio according to the method of the present invention was for brown rice and white rice, but for other grains such as wheat, beans, corn, etc. It goes without saying that it can be calculated.
- the method for calculating the weight ratio of rice, wheat, beans, corn, and other grains according to the present invention even if the weight ratio is calculated using the quality discrimination result by the grain appearance quality discrimination device, The weight ratio can be calculated with high accuracy and is very useful.
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Abstract
Description
上記各重量比率を算出するには、脱ぷした穀粒を一粒ずつ、整粒と屑粒とに選別し、あるいは整粒と胴割粒、未熟粒、死米、着色粒、胴割粒以外の被害粒等に選別し、該選別した穀粒を計量する必要があり、手間と時間のかかるものである。
上記穀粒外観品位判別装置は、例えばスキャナーを利用して1000粒程度のサンプル粒を一度に撮像し、該撮像して得られた画像情報を利用して該サンプル粒個々の品位を判別するものであり、穀物の品位を簡易に評価できる装置である(特許文献1,2参照。)。
(1)撮像処理(S11)
穀粒外観品位判別装置は、評価対象となる穀粒のサンプル粒を撮像し、該サンプル粒の撮像データを取得する。
(2)データ処理(S12)
穀粒外観品位判別装置は、前記撮像データに基づいてサンプル粒の品位に関連するデータを抽出する。
(3)品位判別処理(S13)
穀粒外観品位判別装置は、前記サンプル粒の品位に関連するデータを予め設定したしきい値と比較して該サンプル粒の品位を判別する。
(4)粒数集計処理(S14)
穀粒外観品位判別装置は、品位の判別したサンプル粒について品位別に粒数を集計する。
(5)重量比率算出処理(S15)
穀粒外観品位判別装置は、前記品位別に集計されるサンプル粒の粒数と予め品位別に設定した一粒当たりの重量換算係数(1粒重)とに基づいて品位別の重量比率を算出する。
(6)出力処理(S16)
穀粒外観品位判別装置は、前記サンプル粒の品位別重量比率の算出値をプリンタやモニタに出力する。
前述のとおり、穀粒外観品位判別装置には、予め判別区分(品位)別に玄米一粒当たりの重量換算係数(1粒重)が設定されている。
そして、穀粒外観品位判別装置は、判別区分(品位)別に集計されたサンプル粒の粒数に前記重量換算係数(1粒重)を掛け合わせることで換算重量を求め、該換算重量の総重量に対する割合を判別区分(品位)別の重量比率として算出する。
上記穀粒外観品位判別装置を利用する方法によれば、穀粒の品位別重量比率を簡易かつ迅速に算出することができる。
図8は二つの砕粒の比較例を示す。
図8(a)に示す砕粒と図8(b)に示す砕粒は、明らかに大きさが異なるものである。
しかしながら、上記従来の穀粒外観品位判別装置を利用する方法は、両者をともに一粒の砕粒として扱い、同じ重量換算係数(1粒重)を掛け合わせて換算重量を求めるものであり、必ずしも精度よく重量比率が算出できるものとはなっていない。
図1は、本発明の方法で使用する穀粒外観品位判別装置の一例を示す。
穀粒外観品位判別装置1は、米、麦、豆、コーン等の穀粒を撮像する撮像手段2と、該撮像手段2とケーブル3で接続される品位判別手段4を備えるものである。前記撮像手段2には例えば市販のスキャナーを用いることができる。また、前記品位判別手段4にはパーソナルコンピュータを用いることができる。
本発明の方法は、玄米のサンプル粒を複数収納した撮像用トレイ5を撮像手段2の撮像台2b上に載置することで開始される。
(1)撮像処理(S1)
まず、穀粒外観品位判別装置1は、前記撮像手段2によって撮像用トレイ5に収納された複数のサンプル粒を撮像し、該サンプル粒の撮像データを取得する。
(2)データ処理(S2)
次に、穀粒外観品位判別装置1は、前記取得した撮像データを品位判別手段4に送り、画像処理によってサンプル粒の外形形状、面積、長さ、幅、色彩、胴割等の品位に関連する情報を抽出する。
(3)品位判別処理(S3)
そして、穀粒外観品位判別装置1は、品位判別手段4において前記品位に関する情報を予め設定したしきい値と比較して各サンプル粒の品位を判別する。
(4)画素数集計処理(S4)
穀粒外観品位判別装置1は、品位を判別したサンプル粒について、品位判別手段4において前記外形形状に基づいて該サンプル粒の画素数を品位別に集計する。
(5)重量比率算出処理(S5)
そして、穀粒外観品位判別装置1は、品位判別手段4において品位別に集計されるサンプル粒の画素数と予め品位別に設定される一画素当たりの重量換算係数(ドット重)とに基づいて品位別の重量比率を算出する。
(6)出力処理(S6)
最後に、穀粒外観品位判別装置1は、前記サンプル粒の品位別重量比率の算出値をディスプレイに出力する。
本発明の方法は、穀粒外観品位判別装置1が、全てのサンプル粒について品位の判別を終了し、全てのサンプル粒について画素数を品位別に集計し、全てのサンプル粒についての品位別重量比率を算出した段階で終了する。
なお、複数の玄米に対する上記各処理は、並行してなされるものでもよいし、一括してなされるものでもよい。
図3に示すように画素数で両者を比較した場合、図3(a)は569画素、図3(b)は74画素となり、大きさが約3倍異なることが分かる。
上記本発明の方法によれば、このように同じ品位に区分される玄米について、大きさの違いを考慮した重量比率の算出が可能となる。
本発明において、穀粒外観品位判別装置1の品位判別手段4には、予め判別区分(品位)別に玄米一画素当たりの重量換算係数(ドット重)が記憶設定されている。
そして、穀粒外観品位判別装置1は、判別区分(品位)別に集計されたサンプル粒のドット数(画素数)に前記重量換算係数(ドット重)を掛け合わせることで換算重量を求め、該換算重量の総重量に対する割合を判別区分(品位)別の重量比率として算出する。
なお、図4における「重量換算係数(ドット数)」は、下位の数値を四捨五入して記載するものであるため、「換算重量」の計算値が実際と若干異なるものとなっている。
図4に示す例では、穀粒として玄米を用いたが、本発明の方法によれば、白米等のその他の穀粒の品位別重量比率も精度よく算出できる。
また、図4に示す例では、判別区分(品位)として日本国内における玄米の一評価区分を用いたが、本発明の方法によれば、他の評価区分、特に中国やその他の国の評価区分においても同様に穀粒の品位別重量比率を精度よく算出できる。その場合、穀粒外観品位判別装置1の品位判別手段4に、当該評価区分の品位を判別するための各種しきい値や前記各品位に対応して求められる穀粒一画素当たりの重量換算係数(ドット重)を予め設定しておけばよいことはいうまでもない。
2 撮像手段(スキャナー)
3 ケーブル
4 品位判別手段(パーソナルコンピュータ)
5 撮像用トレイ
11,12 砕粒
15 画素
Claims (2)
- 撮像手段により穀粒を撮像し、該撮像データに基づいて穀粒の品位を判別する穀粒外観品位判別装置における品位別重量比率の算出方法において、
複数の穀粒を撮像し、
該撮像データに基づいて前記複数の穀粒の品位を判別し、
該品位を判別された複数の穀粒の前記撮像データにおける画素数を品位別に集計し、
該品位別に集計された画素数に予め品位別に設定される一画素当たりの重量換算係数を掛け合わせることで前記画素数を品位別の重量に換算し、
該品位別の重量に基づいて当該穀粒の品位別重量比率を算出すること、
を特徴とする穀粒外観品位判別装置における品位別重量比率の算出方法。 - 前記穀粒を撮像する撮像手段は画像読取装置である請求項1記載の穀粒外観品位判別装置における品位別重量比率の算出方法。
Priority Applications (5)
Application Number | Priority Date | Filing Date | Title |
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EP11783226.1A EP2573549A4 (en) | 2010-05-19 | 2011-05-10 | Method for calculating weight ratio by quality in grain appearance quality discrimination device |
BR112012024765-4A BR112012024765B1 (pt) | 2010-05-19 | 2011-05-10 | Método para o cálculo de razão de peso por grau de qualidade em dispositivo de discriminação de grau de qualidade de aparência de grão |
CN201180011609.3A CN102782481B (zh) | 2010-05-19 | 2011-05-10 | 谷粒外观品质判别装置的按品质划分的重量比率的计算方法 |
US13/639,270 US8995709B2 (en) | 2010-05-19 | 2011-05-10 | Method for calculating weight ratio by quality grade in grain appearance quality grade discrimination device |
KR20127025990A KR101509130B1 (ko) | 2010-05-19 | 2011-05-10 | 곡립 외관 품위 판별장치에서의 품위별 중량 비율의 산출방법 |
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Publication number | Priority date | Publication date | Assignee | Title |
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WO2014002636A1 (ja) * | 2012-06-27 | 2014-01-03 | 株式会社サタケ | 穀粒外観測定装置 |
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WO2021249995A1 (en) | 2020-06-10 | 2021-12-16 | Bayer Aktiengesellschaft | Azabicyclyl-substituted heterocycles as fungicides |
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Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH0733151A (ja) | 1993-07-06 | 1995-02-03 | Mitsubishi Chem Corp | 包装袋及びその製造方法 |
JPH0733151Y2 (ja) * | 1989-06-08 | 1995-07-31 | 静岡製機株式会社 | 米粒品質判定装置 |
JP2000206054A (ja) * | 1999-01-12 | 2000-07-28 | Fuji Xerox Co Ltd | 印刷物判別装置 |
JP2003090800A (ja) * | 2001-09-19 | 2003-03-28 | Yamamoto Co Ltd | 穀粒画像読取装置用試料整列器 |
JP2003090799A (ja) | 2001-09-19 | 2003-03-28 | Yamamoto Co Ltd | 穀粒画像読取装置用試料整列治具及びこれを用いた試料整列方法 |
JP2003098096A (ja) * | 2001-09-26 | 2003-04-03 | Yamamoto Co Ltd | 穀粒画像読取装置 |
JP2008298695A (ja) | 2007-06-01 | 2008-12-11 | Satake Corp | 穀粒品位判別装置 |
Family Cites Families (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4975863A (en) * | 1988-06-16 | 1990-12-04 | Louisiana State University And Agricultural And Mechanical College | System and process for grain examination |
JPH0751247B2 (ja) * | 1992-09-09 | 1995-06-05 | 工業技術院長 | 非晶質金属箔の張出し・絞り加工法 |
US5917927A (en) * | 1997-03-21 | 1999-06-29 | Satake Corporation | Grain inspection and analysis apparatus and method |
JP3335871B2 (ja) * | 1997-04-23 | 2002-10-21 | 株式会社クボタ | 穀物処理方法及び穀物処理設備 |
TW539853B (en) | 2001-09-10 | 2003-07-01 | Yamagataken | Grain quality judging sample container, grain quality judger, grain quality judging system, grain image reading device, sample arraying jig for the grain image reading device, sample arraying method, and sample arrayer for the grain image reading device |
CN1281952C (zh) * | 2003-10-15 | 2006-10-25 | 中国农业大学 | 一种整精米自动识别的方法 |
KR100903704B1 (ko) | 2007-10-01 | 2009-06-19 | 대한민국 | 쌀 및 현미의 외관 품위 측정장치 및 그 방법 |
CN101234381B (zh) * | 2008-03-07 | 2011-09-07 | 天津市华核科技有限公司 | 基于视觉识别的颗粒物料分选分级方法 |
CN101556250A (zh) * | 2008-04-11 | 2009-10-14 | 郭上鲲 | 产品质量的检验系统及其方法 |
TWI375795B (en) * | 2008-09-19 | 2012-11-01 | Univ Nat Taiwan | Method for determining the geographic origin of koshihikari cultivated in taiwan and foreign countries by appearance properties, chemical components, and physicochemical properties |
KR100925209B1 (ko) | 2009-07-08 | 2009-11-06 | 주식회사 아이디알시스템 | 곡물 색채선별기의 매니폴드 |
-
2010
- 2010-05-19 JP JP2010115425A patent/JP5533245B2/ja active Active
-
2011
- 2011-04-29 TW TW100115198A patent/TWI507675B/zh active
- 2011-05-10 BR BR112012024765-4A patent/BR112012024765B1/pt active IP Right Grant
- 2011-05-10 KR KR20127025990A patent/KR101509130B1/ko active IP Right Grant
- 2011-05-10 US US13/639,270 patent/US8995709B2/en active Active
- 2011-05-10 EP EP11783226.1A patent/EP2573549A4/en not_active Ceased
- 2011-05-10 CN CN201180011609.3A patent/CN102782481B/zh active Active
- 2011-05-10 WO PCT/JP2011/002583 patent/WO2011145287A1/ja active Application Filing
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH0733151Y2 (ja) * | 1989-06-08 | 1995-07-31 | 静岡製機株式会社 | 米粒品質判定装置 |
JPH0733151A (ja) | 1993-07-06 | 1995-02-03 | Mitsubishi Chem Corp | 包装袋及びその製造方法 |
JP2000206054A (ja) * | 1999-01-12 | 2000-07-28 | Fuji Xerox Co Ltd | 印刷物判別装置 |
JP2003090800A (ja) * | 2001-09-19 | 2003-03-28 | Yamamoto Co Ltd | 穀粒画像読取装置用試料整列器 |
JP2003090799A (ja) | 2001-09-19 | 2003-03-28 | Yamamoto Co Ltd | 穀粒画像読取装置用試料整列治具及びこれを用いた試料整列方法 |
JP2003098096A (ja) * | 2001-09-26 | 2003-04-03 | Yamamoto Co Ltd | 穀粒画像読取装置 |
JP2008298695A (ja) | 2007-06-01 | 2008-12-11 | Satake Corp | 穀粒品位判別装置 |
Non-Patent Citations (1)
Title |
---|
See also references of EP2573549A4 |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2014002636A1 (ja) * | 2012-06-27 | 2014-01-03 | 株式会社サタケ | 穀粒外観測定装置 |
JP2014006215A (ja) * | 2012-06-27 | 2014-01-16 | Satake Corp | 穀粒外観測定装置 |
US9607368B2 (en) | 2012-06-27 | 2017-03-28 | Satake Corporation | Grain appearance measuring apparatus |
WO2021233861A1 (en) | 2020-05-19 | 2021-11-25 | Bayer Aktiengesellschaft | Azabicyclic(thio)amides as fungicidal compounds |
WO2021249995A1 (en) | 2020-06-10 | 2021-12-16 | Bayer Aktiengesellschaft | Azabicyclyl-substituted heterocycles as fungicides |
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BR112012024765A2 (pt) | 2016-06-07 |
CN102782481B (zh) | 2015-01-21 |
KR20120127670A (ko) | 2012-11-22 |
JP2011242284A (ja) | 2011-12-01 |
TW201144795A (en) | 2011-12-16 |
TWI507675B (zh) | 2015-11-11 |
US8995709B2 (en) | 2015-03-31 |
EP2573549A4 (en) | 2017-12-27 |
KR101509130B1 (ko) | 2015-04-07 |
EP2573549A1 (en) | 2013-03-27 |
CN102782481A (zh) | 2012-11-14 |
JP5533245B2 (ja) | 2014-06-25 |
US20130051622A1 (en) | 2013-02-28 |
BR112012024765B1 (pt) | 2020-03-24 |
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