CN102759527A - Method for detecting alkali digestion degree of rice - Google Patents
Method for detecting alkali digestion degree of rice Download PDFInfo
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- CN102759527A CN102759527A CN2011101083347A CN201110108334A CN102759527A CN 102759527 A CN102759527 A CN 102759527A CN 2011101083347 A CN2011101083347 A CN 2011101083347A CN 201110108334 A CN201110108334 A CN 201110108334A CN 102759527 A CN102759527 A CN 102759527A
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Abstract
本发明公开了一种检测大米碱消度的方法,包括:首先,制作获取米粒图像背景滤纸;然后,进行米粒碱消度测定,并获取样品图像;接着,利用图像处理方法获取米粒图像面积;接下来,由图像面积得到大米碱消度。本检测方法,在获取大米图片后,能客观表征大米碱消度。The invention discloses a method for detecting alkali depletion of rice, comprising: firstly, making a background filter paper for obtaining an image of rice grains; then, measuring the alkali depletion of rice grains, and obtaining a sample image; then, using an image processing method to obtain the image area of rice grains; Next, the alkali passivity of rice was obtained from the image area. This detection method can objectively characterize the alkali digestion of rice after obtaining the rice picture.
Description
技术领域 technical field
本发明涉及一种检测大米碱消度的方法,它是一种基于计算机图像识别的检测方法;属于计算机图像处理技术领域。The invention relates to a method for detecting alkali depletion of rice, which is a detection method based on computer image recognition and belongs to the technical field of computer image processing.
技术背景 technical background
碱消度是一种简单、快速而准确的间接测定大米糊化温度的方法。碱消度主要由米粒对碱的抵抗性决定,也与米组织的碱度、致密度有关。碱消度分级一般以人工目测,判断米粒散裂度和清晰度。散裂度主要反映米粒在碱溶液中膨胀、消散等特性。清晰度主要以经过碱溶液浸泡后米粒垩白状况、絮状物质的变化为依据。这些方法判断主要以人的主观判断为主,不利于客观反映大米碱消度状况。Alkaline digestion is a simple, rapid and accurate method for indirect determination of rice gelatinization temperature. Alkaline digestion is mainly determined by the resistance of rice grains to alkali, and is also related to the alkalinity and density of rice tissue. Alkaline digestion is generally classified by manual visual inspection to judge the degree of spallation and clarity of rice grains. The degree of spallation mainly reflects the characteristics of rice grains such as swelling and dissipating in alkaline solution. Clarity is mainly based on the chalky state of rice grains and changes in flocculent substances after soaking in alkaline solution. The judgment of these methods is mainly based on people's subjective judgment, which is not conducive to objectively reflecting the alkali depletion status of rice.
发明内容 Contents of the invention
为解决大米碱消度的客观定量检测问题,本发明提出一种利用图像处理技术客观检测大米碱消度的方法。In order to solve the problem of objective and quantitative detection of rice alkali digestion, the present invention proposes a method for objectively detecting rice alkali digestion using image processing technology.
本发明所述的检测碱消度的方法,包括以下步骤:The method for detecting alkali digestion of the present invention comprises the following steps:
步骤一、制作获取米粒图像背景滤纸;Step 1, making the background filter paper for obtaining the image of rice grains;
步骤二、米粒碱消度测定,并获取样品图像;Step 2: Measuring the alkali digestion of rice grains, and obtaining the image of the sample;
步骤三、利用图像处理方法获取米粒图像面积;Step 3, using the image processing method to obtain the area of the rice grain image;
步骤四、由图像面积得到大米碱消度。Step 4: Obtain the alkali passivity of rice from the area of the image.
如上所述的检测碱消度的方法,所述的步骤一中制作碱消度测定过程中图像背景,将滤纸剪为直径55mm圆形滤纸,并使用黑色墨水将其染成黑色。In the method for detecting alkali digestion as described above, in the first step, the image background during the measurement of alkali digestion is made, the filter paper is cut into a circular filter paper with a diameter of 55mm, and it is dyed black with black ink.
如上所述的检测碱消度的方法,所述的步骤二中,将黑色滤纸置于内径为55mm培养皿中对碱消度进行测定。使用扫描仪分别获取初始米粒图片和氢氧化钾浸泡后米粒图片,保存图片。In the method for detecting alkali digestion as described above, in the second step, the black filter paper is placed in a petri dish with an inner diameter of 55 mm to measure the alkali digestion. Use the scanner to obtain the initial rice grain picture and the rice grain picture after potassium hydroxide soaking respectively, and save the picture.
如上所述的检测碱消度的方法,所述的步骤三中使用图像处理软件分别对初始米粒图片和氢氧化钾浸泡后米粒图片进行图像预处理,得到处理后的米粒图片,计算米粒图像面积。In the method for detecting alkali digestion as described above, image processing software is used to perform image preprocessing on the initial rice grain picture and the rice grain picture soaked in potassium hydroxide in the step 3, to obtain the processed rice grain picture, and to calculate the area of the rice grain image .
如上所述的检测碱消度的方法,所述的步骤四中将氢氧化钾浸泡后米粒面积除以初始米粒图像面积,以此反映大米碱消度。In the above-mentioned method for detecting alkali digestion, in step 4, the area of rice grains soaked in potassium hydroxide is divided by the area of the initial rice grain image, so as to reflect the alkali digestion of rice.
本发明所提出的方法,通过以黑色为背景获取初始米粒图片和氢氧化钾浸泡后米粒图片,利用大米在碱溶液中浸泡后导致米粒图像面积不同的原理,通过计算碱溶液浸泡后米粒图像面积除以初始图像面积的比值来测定其碱消度。本方法在样品检测时,通过扫描仪获取米粒图片,代替传统方法中以人主观判断分级的方法,可以客观评价碱消度差异,减少主观随意性;并且可以一次性检测多个样品。The method proposed by the present invention obtains the initial rice grain picture and the rice grain picture after soaking in potassium hydroxide by using black as the background, utilizes the principle that rice grain image areas are different after soaking in an alkali solution, and calculates the rice grain image area after soaking in an alkali solution Divide by the ratio of the initial image area to determine its alkali passivity. The method uses a scanner to obtain pictures of rice grains during sample detection, replacing the traditional method of grading based on human subjective judgment, which can objectively evaluate the difference in alkali passivity and reduce subjective randomness; moreover, multiple samples can be detected at one time.
具体实施方式 Detailed ways
下面通过具体得的实施例对本发明方法进行说明。The method of the present invention will be described below through specific examples.
本发明实施例所述方法的详细步骤说明如下:The detailed steps of the method described in the embodiment of the present invention are as follows:
首先,将滤纸剪为直径55mm圆形滤纸,并置于黑色墨水中12h。然后将滤纸取出,在阴凉环境下晾干。用蒸馏水浸泡滤纸若干次至水无黑色出现。将黑色滤纸晾干。First, cut the filter paper into a circular filter paper with a diameter of 55mm, and put it in black ink for 12h. Then remove the filter paper and let it dry in a cool environment. Soak the filter paper several times with distilled water until no black color appears in the water. Dry the black filter paper.
然后,将上述黑色滤纸置于内径为55mm培养皿中,7粒加工精度为二级的大米等距离按径向分布于培养皿中,注入10mL氢氧化钾溶液(籼米1.7g/100mL,粳米1.4g/100mL)。扫描仪已分辨率为300dpi扫描米粒RGB图片,保存图片。培养皿加盖,在恒定室温下(25℃)静置23h。扫描仪获取浸泡后米粒RGB图片,保存图片。Then, the above-mentioned black filter paper was placed in a petri dish with an inner diameter of 55 mm, and 7 grains of rice with a processing precision of second grade were equidistantly distributed in the petri dish in a radial direction, and injected with 10 mL of potassium hydroxide solution (1.7 g/100 mL for indica rice, 1.4 g/100 mL for japonica rice). g/100mL). The scanner has scanned the rice grain RGB picture with a resolution of 300dpi and saved the picture. Cover the petri dish and let it stand at constant room temperature (25°C) for 23h. The scanner obtains the RGB picture of rice grains after soaking and saves the picture.
接着,使用图像处理软件分别对初始米粒图片和氢氧化钾浸泡23h后米粒图片进行按照gray=0.2989×R+0.5870×G+0.1140×B灰度转换、以[3,3]的滤波器进行中值滤波、使用Ostu自适应阈值确定的分割阈值进行二值化处理、以半径为2的圆形结构元素对二值图像进行形态学开操作,得到处理后的米粒二值图片,通过二值图像分别计算初始米粒图片和浸泡23h后米粒图片7粒米图像面积和。Next, use the image processing software to convert the initial rice grain picture and the rice grain picture soaked in potassium hydroxide for 23 hours according to gray=0.2989×R+0.5870×G+0.1140×B grayscale conversion, and use the filter of [3,3] Value filtering, using the segmentation threshold determined by the Ostu adaptive threshold for binarization processing, and performing morphological opening operations on the binary image with a circular structural element with a radius of 2, to obtain the processed binary image of rice grains, through the binary image Calculate the initial rice grain picture and the 7-grain image area sum of the rice grain picture after soaking for 23 hours.
接下来,用浸泡23h后米粒面积除以初始米粒图像面积得到的比值判断其碱消度(1-7级),其中1级为1.0-1.4、2级为1.4-2.0、3级为2.0-2.6、4级为2.8-3.4、5级为3.4-4.0、6级为4.0-5.0、7级为5.0以上。Next, use the ratio obtained by dividing the area of rice grains after soaking for 23 hours by the area of the initial image of rice grains to judge its alkali digestion (grade 1-7), of which grade 1 is 1.0-1.4, grade 2 is 1.4-2.0, grade 3 is 2.0- 2.6, 2.8-3.4 for grade 4, 3.4-4.0 for grade 5, 4.0-5.0 for grade 6, and above 5.0 for grade 7.
最后所应说明的是:以上实施例仅用以说明而非限制本发明的技术方案,尽管参照上述实施例对本发明进行了详细说明,本领域的普通技术人员应当理解:依然可以对本发明进行修改或者等同替换,而不脱离本发明精神和范围的任何修改或局部替换,其均应涵盖在本发明的权利要求范围当中。Finally, it should be noted that the above embodiments are only used to illustrate and not limit the technical solutions of the present invention, although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: the present invention can still be modified Or an equivalent replacement, any modification or partial replacement without departing from the spirit and scope of the present invention shall fall within the scope of the claims of the present invention.
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CN111289512A (en) * | 2020-02-28 | 2020-06-16 | 中国水稻研究所 | Rice grain alkali elimination value high-throughput determination method based on deep convolutional neural network |
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Non-Patent Citations (4)
Title |
---|
SARUN SUMRIDDETCHKAJORN ET AL.: "Identification of Thai Hom Mali Rice using a Refractometer", 《SENSING FOR AGRICULTURE AND FOOD QUALITY AND SAFETY》 * |
蒲一涛等: "碱消度法快速测定泰国香米纯度", 《深圳大学学报(理工版)》 * |
陈志行等: "大米品质分析中的碱消度法优化研究", 《粮食与饲料工业》 * |
马涛: "《粮油食品检验》", 31 March 2009, 化学工业出版社 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
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CN111289512A (en) * | 2020-02-28 | 2020-06-16 | 中国水稻研究所 | Rice grain alkali elimination value high-throughput determination method based on deep convolutional neural network |
CN111289512B (en) * | 2020-02-28 | 2021-04-13 | 中国水稻研究所 | A high-throughput determination method of rice grain alkalinity value based on deep convolutional neural network |
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