WO2022228033A1 - 图像偏色的检测及校正方法、设备及冰箱 - Google Patents

图像偏色的检测及校正方法、设备及冰箱 Download PDF

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WO2022228033A1
WO2022228033A1 PCT/CN2022/084707 CN2022084707W WO2022228033A1 WO 2022228033 A1 WO2022228033 A1 WO 2022228033A1 CN 2022084707 W CN2022084707 W CN 2022084707W WO 2022228033 A1 WO2022228033 A1 WO 2022228033A1
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image
color cast
detection
area
camera
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PCT/CN2022/084707
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English (en)
French (fr)
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毕研华
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青岛海尔电冰箱有限公司
海尔智家股份有限公司
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Publication of WO2022228033A1 publication Critical patent/WO2022228033A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/20—Image preprocessing
    • G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/56—Extraction of image or video features relating to colour
    • 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
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • 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
    • G06T2207/20—Special algorithmic details
    • G06T2207/20092—Interactive image processing based on input by user
    • G06T2207/20104—Interactive definition of region of interest [ROI]

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  • the invention relates to the field of home appliances, and in particular, to a method, device and refrigerator for detecting and correcting image color cast.
  • Color is one of the important features of images, and is usually an important basis for image processing and analysis. It is of great significance for research in computer vision fields such as target recognition and detection, image segmentation, and video retrieval.
  • the color of an object is determined by its reflectivity characteristics. Due to the color constancy of the human visual system, the influence of factors such as lighting conditions on the color can be eliminated to a certain extent.
  • the imaging device does not have this "adjustment" function and will be affected by The influence of factors such as the external light environment and the characteristics of the imaging photosensitive components themselves cause a certain degree of error between the image color and the real color of the object, that is, "color cast".
  • the photosensitive components cannot obtain a normally exposed image, which will also cause the image color to be too dark or too explosive. If the image color cast is not detected and calibrated in a timely and effective manner, the color-based image vision algorithm may not work.
  • the purpose of the present invention is to provide an image color cast detection and correction method, equipment and refrigerator.
  • an embodiment of the present invention provides a method for detecting and correcting color cast of an image, and the method includes:
  • the color cast of the image is automatically corrected by adjusting the brightness of the fill light disposed around the camera.
  • performing color cast detection based on HSV space on an area specifically includes:
  • the method further includes:
  • the "automatic correction of the color cast of the image by adjusting the brightness of the fill light set around the camera” specifically includes:
  • the fill light is a plurality of LED lights distributed around the camera according to a certain rule.
  • the distance between the fill light and the camera is in the range of 20-40 cm.
  • the method further includes:
  • a photographed image of a yogurt special area inside the refrigerator is obtained as an image to be detected, wherein the yogurt special area includes a bottle holder for placing yogurt.
  • the N ROI regions are distributed around the bottle holder of the image to be detected.
  • an embodiment of the present invention provides an electronic device, including a memory and a processor, where the memory stores a computer program that can run on the processor, and the processor executes the program At the same time, the steps in any one of the above-mentioned methods for detecting and correcting color cast of an image are implemented.
  • an embodiment of the present invention provides a refrigerator, which includes the above-mentioned electronic device.
  • the image color cast detection and correction method of the present invention can quickly detect whether the image has color cast, and the detection accuracy is high; and after detecting the image color cast, automatically adjust the fill light. The brightness of the light is automatically corrected for the color cast of the image.
  • FIG. 1 is a schematic flowchart of a method for detecting and correcting color cast of an image according to the present invention.
  • FIG. 2 is a schematic diagram of the distribution of the ROI region in the image to be detected according to the present invention.
  • FIG. 3 is a partial structural schematic diagram of the interior of the refrigerator of the present invention.
  • refrigerator 1. yogurt area; 3. first bottle holder; 4. second bottle holder; 5. camera and fill light; 6. image to be detected; 7. ROI area.
  • the yogurt area is set up in the refrigerator, and the yogurt can be monitored centrally.
  • the yogurt area is provided with a bottle holder, and the yogurt is placed in the bottle holder.
  • the camera will be blocked by colored plastic bags or the like, causing the color of the light to change, resulting in a color cast in the captured image, which affects the accuracy of image recognition.
  • the present invention provides a method for detecting and correcting the color cast of an image, which can quickly detect whether there is a color cast in an image, and the detection accuracy is high; and after detecting the color cast in the image, automatically adjust the fill light The brightness of the light is automatically corrected for the color cast of the image.
  • the method includes:
  • Step S100 crop multiple ROI regions of the image to be detected to obtain N ROI regions, where N is a positive integer greater than 1.
  • the present invention mainly detects the color cast of the image of the yogurt special area in the refrigerator. Therefore, the photographed image of the yogurt special area in the refrigerator is obtained as the image to be detected, wherein the yogurt special area includes a bottle holder for placing yogurt.
  • the N ROI regions are distributed around the bottle holder of the image to be detected. Since the inside of the bottle holder is used to place yogurt, after the yogurt is placed, the bottle holder is partially covered by the yogurt, which cannot provide a stable environment for color cast detection. Therefore, the surrounding area of the bottle holder that will not be blocked by yogurt is selected as the ROI area for detection, which will not be affected by the placed yogurt. And because the N ROI areas are distributed around the bottle holder, even if a color cast appears in part of the image, it can be detected, and the detection accuracy is high.
  • Step S200 Perform color cast detection based on HSV space on the N regions respectively, and if at least one of the N regions has a color cast, it is determined that the image to be detected has a color cast.
  • the user can also be notified to remove the abnormal situation manually (for example, if the camera is blocked by a colored plastic bag, the user can remove the colored plastic bag).
  • HSV Hue, Saturation, Value
  • S Saturation
  • V Lightness
  • the color cast detection of the regional image based on the HSV space of the present invention specifically includes:
  • Step S210 Read in the region image in RGB space.
  • the RGB color space is based on the three basic colors of R (Red: red), G (Green: green), and B (Blue: blue), which are superimposed to different degrees to produce rich and extensive colors, so it is commonly known as the three-primary color mode.
  • Step S220 Convert the image of the RGB color channel to the HSV channel.
  • Step S230 Perform channel segmentation on the image, which is divided into three channel data of H, S, and V respectively.
  • Step S240 Calculate the average value of the H, S, and V channel data of all the pixels of the image respectively.
  • Calculate the average value of the H channel data, the average value of the S channel data, and the average value of the V channel data of all pixels of the image, and the three average values are used to characterize the area image in the three channels. composite value.
  • Step S250 If at least one of the three average values is not within the set value range, it is determined that there is a color cast in the area image.
  • the initial average value of all pixels in each area in each channel can be obtained through the captured pictures, and the value of the average value of all pixels in the three channels of the image area can be set through the initial average value. scope.
  • the initial average values of the H, S, and V channel data of all pixels in the image area are obtained, according to the three initial average values. , and set the value range of the average value of all pixels in the three channels of the image area.
  • Step S300 After it is determined that the image to be detected has color cast, the color cast of the image is automatically corrected by adjusting the brightness of the fill light disposed around the camera.
  • the fill light of the present invention preferably adopts an LED light that emits white light.
  • the LED light is gradually brightened, the gradually increasing white light will weaken other colored light, so as to achieve the purpose of correcting the color cast.
  • the "automatically correcting the color cast of the image by adjusting the brightness of the fill light set around the camera” specifically includes:
  • Step S310 While gradually increasing the brightness of the fill light, control the camera to periodically capture images and detect whether the captured image has a color cast.
  • the brightness of the fill light is gradually increased, and at the same time, images are captured periodically (the interval between two adjacent cycles is short), and the methods of steps S100 and S200 are used to detect whether the newly captured image has color cast.
  • Step S320 After detecting that the image captured by the camera has no color cast, stop increasing the brightness of the fill light.
  • the yogurt special area includes a first bottle seat, the first bottle seat is used for placing yogurt, and the camera and the fill light are arranged on the second bottle seat.
  • the camera and the fill light are on the same level, and the fill light is a plurality of LED lights distributed around the camera according to a certain rule.
  • the plurality of fill lights are distributed in a rectangle or circle, and the camera is arranged in the middle of the rectangle or circle.
  • the multiple fill lights emit downward parallel beams, which can reduce or prevent the generation of shadows while filling the light.
  • the distance between the fill light and the camera is in the range of 20-40 cm.
  • a camera and a fill light are arranged at the bottom of the second bottle holder of the refrigerator, and the camera is used to capture an image of the yogurt special area located at the bottom of the second bottle holder, and the yogurt special area includes a yogurt area.
  • the first bottle holder. The image captured by the camera is used as the image to be detected, and the area around the bottle holder of the image to be detected is cropped to obtain N ROI regions, and the distribution of the N ROI regions is shown in FIG. 2 . Then, color cast detection based on the HSV space is performed on the N regions respectively, and if at least one of the N regions has a color cast, it is determined that the image to be detected has a color cast.
  • the brightness of the fill light is gradually increased, and at the same time, the image is periodically captured, and the above-mentioned color cast detection method is used to continuously detect whether the newly captured image has a color cast. After detecting that the image captured by the camera has no color cast, stop increasing the brightness of the fill light. Finally, when the image recognition is completed, turn off the fill light.
  • the present invention provides a method for detecting and correcting color cast of an image.
  • N ROI areas are obtained, and then the color cast detection based on HSV space is performed on these ROI areas.
  • the color cast detection result of the region obtains the color cast detection result of the image to be detected, and the detection method can quickly and accurately detect the image to be detected.
  • the brightness of the fill light can be automatically adjusted, and the color cast of the image can be automatically corrected, so that the accuracy of image recognition is not affected by the color cast.
  • the present invention also provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor implements the above-mentioned detection of color cast of the image when the program is executed and any one of the steps in the correction method, that is, to implement the steps in any one of the technical solutions in the above-mentioned image color cast detection and correction method.
  • the present invention also provides a refrigerator, which includes the above-mentioned electronic device.
  • the refrigerator further includes a special area for yogurt, a first bottle seat and a second bottle seat, and a camera and a fill light are arranged at the bottom of the second bottle seat.
  • the camera and the fill light The lights are on the same horizontal plane, and the fill light is a plurality of LED lights distributed in a rectangle around the camera, and the camera is arranged in the middle of the rectangle.
  • the multiple fill lights emit downward parallel beams, which can reduce or prevent the generation of shadows while filling the light.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
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  • Computer Vision & Pattern Recognition (AREA)
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  • Image Analysis (AREA)

Abstract

本发明揭示了一种图像偏色的检测及校正方法、设备及冰箱，方法包括：对图像的多个ROI区域进行裁剪，得到N个ROI区域；分别进行偏色检测，若至少一个区域出现偏色，则判定图像出现偏色，通过调整补光灯的亮度，对图像的偏色进行自动校正，能够快速对图像是否存在偏色进行检测，检测到出现偏色后，自动对图像的偏色进行校正。

Description

图像偏色的检测及校正方法、设备及冰箱 技术领域
本发明涉及家电领域，特别涉及一种图像偏色的检测及校正方法、设备及冰箱。
背景技术
颜色是图像的重要特征之一，通常也是图像处理和分析的重要依据，尤其对于目标识别与检测、图像分割和视频检索等计算机视觉领域的研究具有十分重要的意义。物体的颜色由其反射率特性所决定，由于人眼视觉系统具有颜色恒常性，能够在一定程度上消除光照条件等因素对颜色的影响，但成像设备不具备这种“调节”功能，会受到外界光环境、成像感光元器件本身的特性等因素的影响，造成图像色彩与物体真实色彩之间存在一定程度上的误差，即“偏色”。同时，当外界光环境过暗或者过亮时，感光元器件无法获取正常曝光的图像，也会造成图像色彩过暗或者过爆的现象。若不及时有效地检测出并校准图像偏色，则使得基于颜色的图像视觉算法可能无法进行。
在冰箱领域，当冰箱内部的灯光被有色塑料袋遮挡，导致光的颜色发生变化时，冰箱内部拍摄的图像会出现严重的偏色，进而影响图像中物体识别的准确率。为了减少上述情况导致的图像识别准确率降低的问题，需要对冰箱内部拍摄的图片进行偏色检测及校正。但是目前现有的偏色检测理论方法，针对冰箱内部拍摄的图像的偏色检测，计算量大且比较耗时，同时准确率低。
因此，亟待提出一种高效、且准确率高的专门针对冰箱内部图像的偏色检测及校正方法。
发明内容
本发明的目的在于提供一种图像偏色的检测及校正方法、设备及冰箱。
为实现上述发明目的之一，本发明一实施方式提供一种图像偏色的检测及校正方法，所述方法包括：
对待检测图像的多个ROI区域进行裁剪，得到N个ROI区域，所述N为大于1的正整数；
分别对所述N个区域进行基于HSV空间的偏色检测，若所述N个区域中至少一个区域出现偏色，则判定所述待检测图像出现偏色；
在判定所述待检测图像出现偏色后，通过调整设置在摄像头周围的补光灯的亮度，对图像的偏色进行自动校正。
作为本发明一实施方式的进一步改进，对一个区域进行基于HSV空间的偏色检测具体包括：
以RGB空间读入所述区域图像；
将RGB颜色通道的图像转换为HSV通道；
对图像进行通道分割，分别分割为H、S、V三个通道数据；
计算所述图像所有像素点分别在H、S、V三个通道数据的平均值；
若所述三个平均值中至少一个平均值不在设定的取值范围内，则判定所述区域图像存在偏色。
作为本发明一实施方式的进一步改进，所述方法还包括：
计算一个图像区域未出现偏色时，所述图像区域的所有像素点分别在H、S、V三个通道数据的初始平均值，根据所述三个初始平均值，设定所述图像区域三个通道所有像素点平均值的取值范围。
作为本发明一实施方式的进一步改进，所述“通过调整设置在摄像头周围的补光灯的亮度，对图像的偏色进行自动校正”具体包括：
在逐渐增加所述补光灯的亮度的同时，控制所述摄像头周期性拍摄图像并检测所述拍摄的图像是否出现偏色；
在检测到摄像头拍摄的图像没有出现偏色后，停止增加补光灯的亮度。
作为本发明一实施方式的进一步改进，所述补光灯为多个按一定规律分布在所述摄像头周围的LED灯。
作为本发明一实施方式的进一步改进，所述补光灯与摄像头的距离在20～40cm范围内。
作为本发明一实施方式的进一步改进，所述方法还包括：
获取拍摄到的冰箱内部酸奶专区的图像作为待检测图像，其中，所述酸奶专区包括有放置酸奶的瓶座。
作为本发明一实施方式的进一步改进，所述N个ROI区域分布在所述待检测图像的瓶座的四周。
为实现上述发明目的之一，本发明一实施方式提供一种电子设备，包括存储器和处理器，所述存储器存储有可在所述处理器上运行的计算机程序，所述处理器执行所述程序时实现上述任意一项所述图像偏色的检测及校正方法中的步骤。
为实现上述发明目的之一，本发明一实施方式提供一种冰箱，所述冰箱包含上述所述的电子设备。
与现有技术相比，本发明的图像偏色的检测及校正方法，能够快速对图像是否存在偏色进行检测，而且检测的精度高；并且在检测到图像出现偏色后，自动调整补光灯的亮度，从而自动对图像的偏色进行校正。
附图说明
图1是本发明的图像偏色的检测及校正方法的流程示意图。
图2是本发明的ROI区域在待检测图像的分布示意图。
图3是本发明的冰箱内部的部分结构示意图。
其中，1、冰箱；2、酸奶专区；3、第一瓶座；4、第二瓶座；5、摄像头和补光灯；6、待检测图像；7、ROI区域。
具体实施方式
以下将结合附图所示的具体实施方式对本发明进行详细描述。但这些实施方式并不限制本发明，本领域的普通技术人员根据这些实施方式所做出的结构、方法、或功能上的变换均包含在本发明的保护范围内。
在冰箱中设置酸奶专区，可以对酸奶进行集中监控。一般酸奶专区设置有瓶座，酸奶放置在瓶座内。在对瓶座内的酸奶进行监控的过程中，需要对酸奶专区进行图像拍摄及识别。但是有时候摄像头会被有色塑料袋之类的遮挡，导致光的颜色发生变化，从而导致拍摄的图像出现偏色，影响图像识别的准确率。
因此，本发明提供一种图像偏色的检测及校正方法，所述方法能够快速对图像是否存在偏色进行检测，而且检测的精度高；并且在检测到图像出现偏色后，自动调整补光灯的亮度，从而自动对图像的偏色进行校正。
如图1所示，所述方法包括：
步骤S100：对待检测图像的多个ROI区域进行裁剪，得到N个ROI区域，所述N为大于1的正整数。
由于对整张图像进行偏色检测时，检测效率低，且准确率低(比如只是1/3区域出现偏色，基于整张图像的偏色检测无法检测出偏色)，因此对待检测图像的多个ROI区域(感兴趣区域)进行裁剪，得到大于1的N个ROI区域。由于裁剪后的ROI区域图像尺寸远小于整张图像的尺寸，因此，对这些ROI区域图像进行偏色检测的 效率高、检测速度快且准确率高。
本发明中主要针对冰箱内酸奶专区的图像的偏色进行检测，因此，获取拍摄到的冰箱内部酸奶专区的图像作为待检测图像，其中，所述酸奶专区包括有放置酸奶的瓶座。
进一步的，如图2所示，所述N个ROI区域分布在所述待检测图像的瓶座的四周。由于瓶座内部用于放置酸奶，在放置酸奶后，瓶座部分被酸奶遮挡，无法为偏色检测提供稳定的环境。因此，选取不会被酸奶遮挡的瓶座的四周区域作为ROI区域进行检测，不会受到放置的酸奶的影响。并且由于这N个ROI区域分布在瓶座的四周，即使图像的部分出现偏色也可检测到，检测的准确率高。
步骤S200：分别对所述N个区域进行基于HSV空间的偏色检测，若所述N个区域中至少一个区域出现偏色，则判定所述待检测图像出现偏色。
如果待检测图像部分区域出现偏色，那么出现偏色的这部分区域的图像识别的准确率就会下降，因此，在检测的过程中，只要一个区域检测到偏色，则判定所述待检测图像出现偏色，需要对图像的偏色进行校正。
需要说明的是，若检测到图像出现偏色，也可以通知用户手动排除异常情况(例如若是因为有色塑料袋遮挡摄像头，则用户可以去掉有色塑料袋)。
HSV(Hue,Saturation,Value)是根据颜色的直观特性由A.R.Smith在1978年创建的一种颜色空间,也称六角锥体模型(Hexcone Model)。这个模型中颜色的参数分别是：色调(H)，饱和度(S)，明度(V)。
本发明的基于HSV空间对区域图像进行偏色检测具体包括：
步骤S210：以RGB空间读入所述区域图像。
RGB颜色空间以R(Red:红)、G(Green:绿)、B(Blue:蓝)三种基本色为基础，进行不同程度的叠加，产生丰富而广泛的颜色，所以俗称三基色模式。
步骤S220：将RGB颜色通道的图像转换为HSV通道。
图像在RGB颜色通道与HSV通道之间的数据转换为现有技术，此处不具体赘述。
步骤S230：对图像进行通道分割，分别分割为H、S、V三个通道数据。
步骤S240：计算所述图像所有像素点分别在H、S、V三个通道数据的平均值。
计算所述图像所有像素点在H通道数据的平均值、在S通道数据的平均值、和在V通道数据的平均值，所述三个平均值用于表征所述区域图像在三个通道的综合值。
步骤S250：若所述三个平均值中至少一个平均值不在设定的取值范围内，则判定所述区域图像存在偏色。
判断是否这三个平均值都在预先设定的取值范围内，只要有一个平均值不在预先设定的取值范围内，则判定所述区域图像存在偏色。
在冰箱出厂前，可以通过拍摄的图片获取各个区域的所有像素点在每个通道的初始平均值，通过所述初始平均值，设定所述图像区域三个通道所有像素点平均值的取值范围。
在一个具体的实施方式中，获取一个图像区域未出现偏色时，所述图像区域的所有像素点分别在H、S、V三个通道数据的初始平均值，根据所述三个初始平均值，设定所述图像区域三个通道所有像素点平均值的取值范围。
步骤S300：在判定所述待检测图像出现偏色后，通过调整设置在摄像头周围的补光灯的亮度，对图像的偏色进行自动校正。
本发明的补光灯优选采用发白光的LED灯，在逐渐调亮LED灯时，逐渐增强的白光会弱化其它的有色光，从而达到对偏色进行校正的目的。
在一个具体的实施方式中，所述“通过调整设置在摄像头周围的补光灯的亮度，对图像的偏色进行自动校正”具体包括：
步骤S310：在逐渐增加所述补光灯的亮度的同时，控制所述摄像头周期性拍摄图像并检测所述拍摄的图像是否出现偏色。
首先逐渐增加补光灯的亮度，同时，周期性(相邻两个周期间隔较短)拍摄图像，并采用步骤S100和步骤S200的方法检测最新拍摄的图像是否出现偏色。
步骤S320：在检测到摄像头拍摄的图像没有出现偏色后，停止增加补光灯的亮度。
当检测到摄像头拍摄的图像没有出现偏色后，说明目前拍摄的图像质量已经达标，可以正常用于图像识别，因此，停止增加补光灯的亮度。当图像识别完成后，关闭补光灯。
在本发明中，摄像头和补光灯的位置，如图3所示，酸奶专区包括第一瓶座，所述第一瓶座用于放置酸奶，摄像头和补光灯设置在第二瓶座的底部，优选摄像头和补光灯在同一水平面上，所述补光灯为多个按一定规律分布在所述摄像头周围的LED灯。具体的，多个补光灯呈矩形或圆形分布，所述摄像头设置在矩形或者圆形的中间。并且多个补光灯发出了向下的平行光束，在补光的同时，减少或预防阴影的产生。
进一步的，优选所述补光灯与摄像头的距离在20～40cm范围内。
在一具体实施方式中，在冰箱的第二瓶座的底部设置摄像头和补光灯，所述摄像头用于拍摄位于第二瓶座底部的酸奶专区的图像，所述酸奶专区包括有放置酸奶的第一瓶座。将所述摄像头拍摄的图像作为待检测图像，对待检测图像的瓶座四周的区域进行裁剪，得到N个ROI区域，所述N个ROI区域的分布如图2所示。然后分别对所述N个区域进行基于HSV空间的偏色检测，若所述N个区域中至少一个区域出现偏色，则判定所述待检测图像出现偏色。在检测到待检测图像出现偏色后，逐渐增加补光灯的亮度，同时，周期性拍摄图像，并采用上述偏色的检测方法不断检测最新拍摄的图像是否出现偏色。在检测到摄像头拍摄的图像没有出现偏色后，停止增加补光灯的亮度。最终当图像识别完成后，关闭补光灯。
本发明的提供图像偏色的检测及校正方法，通过对待检测图片中瓶座四周的区域进行裁剪，得到N个ROI区域，然后对这些ROI区域进行基于HSV空间的偏色检测，最终根据各个ROI区域的偏色检测结果得到待检测图像的偏色检测结果，所述检测方法能够快速、准确的对待检测图像进行检测。并且在检测出图像出现偏色后，能够自动调整补光灯的亮度，对图像的偏色进行自动校正，从而不因为偏色影响图像识别的准确率。
本发明还提供一种电子设备，包括存储器和处理器，所述存储器存储有可在所述处理器上运行的计算机程序，所述处理器执行所述程序时实现上述所述图像偏色的检测及校正方法中的任意一个步骤，也就是说，实现上述所述图像偏色的检测及校正方法中任意一个技术方案中的步骤。
本发明还提供一种冰箱，包括上述所述的电子设备。
优选的，如图3所示，所述冰箱还包括有酸奶专区，第一瓶座和第二瓶座，所述第二瓶座的底部设置有摄像头和补光灯，所述摄像头和补光灯在同一水平面上，并且所述补光灯为多个按矩形分布在所述摄像头周围的LED灯，所述摄像头设置所述矩形的中间。并且多个补光灯发出了向下的平行光束，在补光的同时，减少或预防阴影的产生。
应当理解，虽然本说明书按照实施方式加以描述，但并非每个实施方式仅包含一个独立的技术方案，说明书的这种叙述方式仅仅是为清楚起见，本领域技术人员应当将说明书作为一个整体，各实施方式中的技术方案也可以经适当组合，形成本领域技术人员可以理解的其他实施方式。
上文所列出的一系列的详细说明仅仅是针对本发明的可行性实施方式的具体说 明，它们并非用以限制本发明的保护范围，凡未脱离本发明技艺精神所作的等效实施方式或变更均应包含在本发明的保护范围之内。

Claims (10)

  1. 一种图像偏色的检测及校正方法，其特征在于，所述方法包括：
    对待检测图像的多个ROI区域进行裁剪，得到N个ROI区域，所述N为大于1的正整数；
    分别对所述N个区域进行基于HSV空间的偏色检测，若所述N个区域中至少一个区域出现偏色，则判定所述待检测图像出现偏色；
    在判定所述待检测图像出现偏色后，通过调整设置在摄像头周围的补光灯的亮度，对图像的偏色进行自动校正。
  2. 根据权利要求1所述图像偏色的检测及校正方法，其特征在于，对一个区域进行基于HSV空间的偏色检测具体包括：
    以RGB空间读入所述区域图像；
    将RGB颜色通道的图像转换为HSV通道；
    对图像进行通道分割，分别分割为H、S、V三个通道数据；
    计算所述图像所有像素点分别在H、S、V三个通道数据的平均值；
    若所述三个平均值中至少一个平均值不在设定的取值范围内，则判定所述区域图像存在偏色。
  3. 根据权利要求2所述图像偏色的检测及校正方法，其特征在于，所述方法还包括：
    计算一个图像区域未出现偏色时，所述图像区域的所有像素点分别在H、S、V三个通道数据的初始平均值，根据所述三个初始平均值，设定所述图像区域三个通道所有像素点平均值的取值范围。
  4. 根据权利要求1所述图像偏色的检测及校正方法，其特征在于，所述“通过调整设置在摄像头周围的补光灯的亮度，对图像的偏色进行自动校正”具体包括：
    在逐渐增加所述补光灯的亮度的同时，控制所述摄像头周期性拍摄图像并检测所述拍摄的图像是否出现偏色；
    在检测到摄像头拍摄的图像没有出现偏色后，停止增加补光灯的亮度。
  5. 根据权利要求4所述图像偏色的检测及校正方法，其特征在于：
    所述补光灯为多个按一定规律分布在所述摄像头周围的LED灯。
  6. 根据权利要求4所述图像偏色的检测及校正方法，其特征在于：
    所述补光灯与摄像头的距离在20～40cm范围内。
  7. 根据权利要求1所述图像偏色的检测及校正方法，其特征在于，所述方法还 包括：
    获取拍摄到的冰箱内部酸奶专区的图像作为待检测图像，其中，所述酸奶专区包括有放置酸奶的瓶座。
  8. 根据权利要求7所述图像偏色的检测及校正方法，其特征在于：
    所述N个ROI区域分布在所述待检测图像的瓶座的四周。
  9. 一种电子设备，包括存储器和处理器，所述存储器存储有可在所述处理器上运行的计算机程序，其特征在于，所述处理器执行所述程序时实现权利要求1-8任意一项所述图像偏色的检测及校正方法中的步骤。
  10. 一种冰箱，其特征在于，所述冰箱包含如权利要求9所述的电子设备。
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