WO2017084391A1 - 一种投影仪图像荧光处理的方法及系统 - Google Patents

一种投影仪图像荧光处理的方法及系统 Download PDF

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WO2017084391A1
WO2017084391A1 PCT/CN2016/093404 CN2016093404W WO2017084391A1 WO 2017084391 A1 WO2017084391 A1 WO 2017084391A1 CN 2016093404 W CN2016093404 W CN 2016093404W WO 2017084391 A1 WO2017084391 A1 WO 2017084391A1
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image
contour
value
ambient light
processing
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PCT/CN2016/093404
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English (en)
French (fr)
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杨伟樑
高志强
许剑波
王梓
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广景视睿科技（深圳）有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/20—Image enhancement or restoration using local operators
    • G06T5/30—Erosion or dilatation, e.g. thinning
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
    • H04N9/3179—Video signal processing therefor
    • H04N9/3182—Colour adjustment, e.g. white balance, shading or gamut
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/70—Denoising; Smoothing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/12—Edge-based segmentation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N9/00—Details of colour television systems
    • H04N9/12—Picture reproducers
    • H04N9/31—Projection devices for colour picture display, e.g. using electronic spatial light modulators [ESLM]
    • 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
    • G06T2207/10064—Fluorescence image

Definitions

  • the present invention relates to the field of projection technology, and in particular, to a method and system for fluorescence processing of a projector image.
  • a projector (also known as a projector) is a device that projects an image or video onto a screen.
  • the image or video projected onto the screen is magnified several times or tens of times while maintaining sharpness. It is convenient for people to watch and gives people an open view. Therefore, the projector is very popular among users.
  • the projection effect of the projected image displayed on the screen is affected by the ambient light in the area where the screen is located. If the ambient light is too strong, the ambient light will over the projector. The projection light makes the screen look white, and the user cannot view the projection screen. If the ambient light is too weak, the projection screen displayed on the screen is too dark, which makes it difficult for people to clearly obtain the information reflected by the projected image.
  • the technical problem to be solved by the present invention is to provide a method and system for fluorescence processing of a projector image, which can realize projection of a fluorescent image by a projection module, wherein the fluorescent image can be distinguished from ambient light, convenient for the user to view the fluorescent image, and can be based on
  • the illumination intensity of the ambient light of the ambient light in the projection area of the projection module adjusts the degree of fluorescence of the fluorescent image, so that the fluorescent image is more in line with the needs of the projection environment.
  • a technical solution adopted by the present invention is to provide a method for fluorescence processing of a projector image, comprising: acquiring a projection image; performing grayscale processing on the projection image to obtain a grayscale image; a degree image, extracting a contour image, and performing an etching expansion process on the contour image; detecting a ring of a projection area in which the projection module performs projection a light intensity of the ambient light, and performing a dye blur process on the image after the corrosion expansion process according to the illumination intensity of the ambient light; and fusing the contour image and the image subjected to the dye blur process to obtain a fluorescence image; A projection module projects the fluorescent image to the projection area.
  • the step of performing grayscale processing on the projected image to obtain a grayscale image includes: acquiring RGB values of pixel points of the projected image; calculating grayscale values according to RGB values of pixel points of the projected image; The RGB value of the pixel of the projected image is replaced with the gradation value to obtain the gradation image.
  • the calculation formula for calculating the gray value of the pixel point is:
  • the Gray is a gray value
  • the R is a color value of a red component of the RGB values of the pixel points
  • the G is a color value of a green component of the RGB values of the pixel points
  • B is the The color value of the blue component in the RGB values of the pixel, the a being a value greater than 0.2 and less than 0.4, the ⁇ being a value greater than 0.5 and less than 0.7, the ⁇ being a value of size 0.1 and less than 0.3.
  • the step of performing a dye blur process on the image after the corrosion expansion process according to the illumination intensity of the ambient light includes: first performing dyeing processing on the image after the corrosion expansion process; and selecting according to the illumination intensity of the ambient light a Gaussian blurred matrix template having a predetermined positive correlation between the Gaussian blurred matrix template and the ambient light illumination intensity; convolving the dyed image with the selected Gaussian blurred matrix template The operation is performed to obtain an image after the dye blur processing.
  • the step of performing an etching expansion process on the contour image includes: extracting a contour edge of each object in the contour image; eliminating a burr of the contour edge, expanding the contour edge, and filling the contour image A blank part inside each object.
  • another technical solution adopted by the present invention is to provide a system for projecting a fluorescent image, comprising a projection module, a light detecting device and a processor, wherein the processor is respectively connected to the projection module and the light detecting device;
  • the processor is configured to: acquire a projection image; perform grayscale processing on the projection image to obtain a grayscale image; and extract from the grayscale image a contour image, and performing an etching expansion process on the contour image; detecting, by the light detecting device, an illumination intensity of ambient light of a projection area projected by the projection module, and performing corrosion expansion processing according to the illumination intensity of the ambient light
  • the image is subjected to a dyeing blurring process; the contour image and the image subjected to the dyeing blurring process are subjected to fusion processing to obtain a fluorescent image; the fluorescent image is transmitted to the projection module, and the projection module is directed to the projection area The fluorescent image is projected.
  • the processor performs grayscale processing on the projected image, and the step of obtaining a grayscale image includes: acquiring RGB values of pixel points of the projected image; and calculating gray according to RGB values of pixel points of the projected image a gradation value obtained by replacing an RGB value of a pixel of the projected image with the gradation value.
  • the calculation formula for calculating the gray value of the pixel point is:
  • the Gray is a gray value
  • the R is a color value of a red component of the RGB values of the pixel points
  • the G is a color value of a green component of the RGB values of the pixel points
  • B is the The color value of the blue component in the RGB values of the pixel, the a being a value greater than 0.2 and less than 0.4, the ⁇ being a value greater than 0.5 and less than 0.7, the ⁇ being a value of size 0.1 and less than 0.3.
  • the step of performing a dye blur process on the image after the corrosion expansion process according to the illumination intensity of the ambient light includes: performing dyeing processing on the image after the corrosion expansion process; and according to the light intensity of the ambient light Selecting a matrix template of Gaussian blurring, the Gaussian fuzzy processed matrix template has a predetermined positive correlation with the illumination intensity of the ambient light; and the volumeized image and the selected Gaussian blurred matrix template are rolled
  • the product operation is performed to obtain an image after the dye blur processing.
  • the step of performing a etch-expanding process on the contour image by the processor includes: extracting a contour edge of each object in the contour image; eliminating burrs of the contour edge, expanding the contour edge, and filling the contour A blank portion inside each object within the image.
  • the beneficial effects of the present invention are: different from the prior art, the present invention is acquired After the image is imaged, the projected image is sequentially subjected to gradation processing to obtain a grayscale image; the contour image is extracted from the grayscale image, and the contour image is subjected to corrosion expansion processing; and the image after the corrosion expansion processing is subjected to dyeing and blurring processing Finally, the contour image and the image subjected to the dyeing and blurring process are merged to obtain a fluorescent image, so that the projection module transmits the fluorescent image to realize the projected fluorescent image, wherein the fluorescent image can be distinguished from the ambient light, and the user can conveniently view the fluorescent image.
  • the illumination intensity of the ambient light in the projection area is performed, specifically, the stronger the illumination intensity of the ambient light, the deeper the degree of blur processing, and the image fluorescence The stronger the intensity of the ambient light, the weaker the degree of blurring, and the weaker the image fluorescence, making the fluorescent image more in line with the needs of the projection environment.
  • FIG. 1 is a schematic view of an embodiment of a system for projecting a fluorescent image of the present invention
  • FIG. 2 is a flow chart of an embodiment of a method for fluorescence processing of a projector image of the present invention
  • FIG. 3 is a flow chart of generating a grayscale image in an embodiment of a method for image fluorescence processing of a projector according to the present invention
  • FIG. 4 is a flow chart of a method for performing dye shading on an image of a method for image fluorescence processing of a projector according to the present invention.
  • a system 20 for projecting a fluorescent image includes a projection module 21, a light detecting device 22, and a processor 23, and the processor 23 is connected to the projection module 21 and the light detecting device 22, respectively.
  • the light detecting device 22 is for detecting the light intensity of the ambient light of the projection area of the projection module 21.
  • the light intensity of ambient light refers to the energy of visible light received per unit area.
  • the gray level of each pixel is worth the illumination intensity of the ambient light of the picture, that is, the illumination intensity of the ambient light in the projection environment.
  • the illumination intensity of the ambient light in the projection environment is, the illumination intensity of the ambient light in the projection environment.
  • Other methods can also be used to detect the ambient light intensity of the projected area, which will not be repeated here.
  • the processor 23 is configured to: acquire a projection image; perform gradation processing on the projection image, obtain a grayscale image, extract a contour image from the grayscale image, perform an etch expansion process on the contour image, and detect the projection module 21 by the light detecting device 22. Performing the illumination intensity of the ambient light in the projected projection area, and performing the dye blur processing on the image after the corrosion expansion processing according to the illumination intensity of the ambient light, and fusing the contour image and the image subjected to the dye blur processing to obtain a fluorescence image, The projection module 21 transmits a fluorescent image and causes the projection module 21 to project a fluorescent image to the projection area.
  • the grayscale image refers to an image having a plurality of levels of color depth between black and white, and R, G, and B are respectively three color values of a red component, a green component, and a blue component of each pixel of the projected image.
  • the color of each pixel in the projected image is determined by three components: R, G, and B, and each component has a median value of 255, so that one pixel can have more than 16 million (255*255*255) color changes. range.
  • the grayscale image is a special color image with the same R, G, and B components. The range of one pixel is 255.
  • the grayscale processing reduces the color of the image from the variable color range to black.
  • the degree value is obtained by replacing the RGB value of the pixel of the projected image with the gray value to obtain a gray image, wherein the calculation formula of the gray value of the pixel is calculated as:
  • Gray is the gray value
  • R is the color value of the red component in the RGB value of the pixel
  • G is the color value of the green component in the RGB value of the pixel
  • B is the color value of the blue component in the RGB value of the pixel
  • ⁇ For values greater than 0.2 and less than 0.4, ⁇ is a value greater than 0.5 and less than 0.7, and ⁇ is a value of 0.1 and less than 0.3. .
  • the contour image refers to an image capable of embodying the contour of each object in the projected image
  • the step of the processor 23 performing the etching expansion processing on the contour image specifically includes extracting the contour edge of each object in the contour image; eliminating the burr of the contour edge and enlarging the contour edge And filling the gaps inside the various objects in the contour image. Specifically, after the burrs of the contour edges are eliminated, the outlines of the respective objects are enlarged, and then the blank portions inside the respective objects in the contour image are filled. Through the above processing, the outline image of the figure becomes smoother, thereby reducing the requirement of specific details in the contour image.
  • the blurring of the image is performed according to the illumination intensity of the ambient light. Specifically, the stronger the illumination intensity of the ambient light, the deeper the blurring process, the weaker the illumination intensity of the ambient light, and the shallower the blurring process, the processor 23 is based on
  • the light intensity of the ambient light is subjected to the process of dyeing and blurring the image after the corrosion expansion process comprises: dyeing the image after the corrosion expansion process, selecting the matrix template of the Gaussian blur process according to the illumination intensity of the ambient light, and the matrix of the Gaussian blur process There is a predetermined positive correlation between the template and the illumination intensity of the ambient light, and the dyed image is convoluted with the selected Gaussian blurred matrix template to obtain the image after the dye blur processing.
  • the predetermined positive correlation between the Gaussian fuzzy matrix template and the ambient light illumination intensity means that the stronger the illumination intensity of the ambient light, the larger the matrix template of the selected Gaussian blur processing, and the Gaussian fuzzy processing matrix.
  • the smaller the fuzzy program is; of course, the predetermined positive correlation between the size of the Gaussian blurred matrix template and the ambient light illumination intensity can be set according to the actual situation.
  • the processor 23 fuses the contour image and the image subjected to the dye blur processing to obtain a foreground image in which the contour image is the image, and the image after the blur processing is used as the background of the image, wherein after the dye blur processing
  • the image is a relatively blurred image that can be contrasted with the contour image, so that the fused image is more prominent and the projection effect is better.
  • the fluorescence can also be applied before the fluorescence image is projected.
  • the image is optimized, for example, smoothing the fluorescence image, improving the quality of the fluorescent image, and the like.
  • the projection image is sequentially subjected to gradation processing to obtain a grayscale image; the contour image is extracted from the grayscale image, and the contour image is subjected to corrosion expansion processing; The image after the corrosion expansion process is subjected to dyeing and blurring processing. Finally, the contour image and the image subjected to the dyeing and blurring process are fused to obtain a fluorescence image, so that the projection module transmits the fluorescence image to realize the projected fluorescence image, wherein the fluorescence image can be combined with the ambient light.
  • the illumination intensity of the ambient light of the projection area is performed, specifically, the stronger the illumination intensity of the ambient light is, the blur
  • the degree of processing the stronger the image fluorescence, the weaker the illumination intensity of the ambient light, the shallower the degree of blurring, and the weaker the image fluorescence, making the fluorescent image more in line with the needs of the projection environment.
  • the present invention further provides an embodiment of a method of projector image fluorescence processing. Please refer to Figure 2, the method includes:
  • Step S201 acquiring a projected image
  • the projected image is provided by an external device or can be extracted from the internal memory of the system.
  • Step S202 performing gradation processing on the projected image to obtain a grayscale image
  • the grayscale image refers to an image with only two colors of black and white, which enables the viewer to more intuitively distinguish the shape and contour of each object in the image.
  • the RGB values of each pixel of the projected image include R value, G value and B value.
  • the color of each pixel in the projected image has three color components of R, G, and B, and each color component has a median value of 255. Such a pixel can have a variation range of more than 16 million (255*255*255) colors.
  • the grayscale image is a special color image with the same R, G, and B components.
  • the range of one pixel is 255.
  • the grayscale processing reduces the color of the image from the variable color range to black.
  • the conversion of the projected image to recovery is to change the RGB value of each pixel in the projected image so that the projected image has only two colors of black and white.
  • step S202 includes:
  • Step S2021 Acquire an RGB value of a pixel of the projected image
  • Step S2022 Calculate a gray value according to an RGB value of a pixel point of the projected image, wherein a calculation formula for calculating a gray value of the pixel point is:
  • Gray is the gray value
  • R is the color value of the red component in the RGB value of the pixel
  • G is the color value of the green component in the RGB value of the pixel
  • B is the color value of the blue component in the RGB value of the pixel
  • ⁇ For values greater than 0.2 and less than 0.4, ⁇ is a value greater than 0.5 and less than 0.7, and ⁇ is a value of 0.1 and less than 0.3.
  • Step S2023 replacing the RGB values of the pixel points of the projected image with the gradation values to obtain a grayscale image.
  • Step S203 extracting a contour image from the grayscale image, and performing a corrosion expansion process on the contour image;
  • the etching expansion process of the contour image is to make the contour of each object in the contour image clearer.
  • the specific step S203 includes: extracting the contour edge of each object in the contour image, eliminating the burr of the contour edge, expanding the contour edge, and filling A blank portion inside each object in the contour image. After the etch and swell process of the contour image, the image is smoother, which can reduce some details in the image.
  • Step S204 detecting the illumination intensity of the ambient light of the projection area projected by the projection module, and performing the dye blur processing on the image after the corrosion expansion process according to the illumination intensity of the ambient light;
  • Step S204 further includes:
  • Step S2041 selecting a matrix template of Gaussian blur processing according to the illumination intensity of the ambient light, and having a predetermined positive correlation between the matrix template of the Gaussian blur processing and the illumination intensity of the ambient light;
  • Gaussian blurred matrix template has a predetermined positive relationship between ambient light and ambient light
  • the correlation relationship is: the stronger the illumination intensity of the ambient light, the larger the matrix template of the selected Gaussian blur processing, and the larger the matrix template of the Gaussian blur processing, the larger the program for blurring the image, the ambient light
  • the predetermined positive correlation between the light intensities of the light can be set according to actual conditions.
  • Step S2042 convolving the dyed image with the selected Gaussian blur processed matrix template to obtain an image after the dye blur processing.
  • Step S205 performing fusion processing on the contour image and the image subjected to the dye blur processing to obtain a fluorescent image
  • the contour image and the image subjected to the dyeing and blurring process are merged to obtain a foreground image with the contour image as the image, and the image after the staining blur processing is used as the background of the image, wherein the image after the dye blur processing is a relatively blurred image.
  • the image can be contrasted with the contour image, so that the fused image is more prominent and the projection effect is better.
  • Step S206 The projection module is caused to project a fluorescent image to the projection area.
  • the fluorescent image may be optimized before the fluorescent image is projected, for example, smoothing the fluorescent image, improving the quality of the fluorescent image, and the like.
  • the projection image is sequentially subjected to gradation processing to obtain a grayscale image; the contour image is extracted from the grayscale image, and the contour image is subjected to corrosion expansion processing; The image after the corrosion expansion process is subjected to dyeing and blurring processing. Finally, the contour image and the image subjected to the dyeing and blurring process are fused to obtain a fluorescence image, so that the projection module transmits the fluorescence image to realize the projected fluorescence image, wherein the fluorescence image can be combined with the ambient light.
  • the illumination intensity of the ambient light of the projection area is performed, specifically, the stronger the illumination intensity of the ambient light is, the blur
  • the degree of processing the stronger the image fluorescence, the weaker the illumination intensity of the ambient light, the shallower the degree of blurring, and the weaker the image fluorescence, making the fluorescent image more in line with the needs of the projection environment.

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Abstract

一种投影仪图像荧光处理的方法及系统，方法包括获取投影图像（S201）；对投影图像进行灰度处理，得到灰度图像（S202）；从灰度图像，提取轮廓图像，并对轮廓图像进行腐蚀膨胀处理（S203）；检测投影模块（21）进行投影的投影区域的环境光的光照强度，并根据环境光的光照强度对腐蚀膨胀处理后的图像进行染色模糊处理（S204）；将轮廓图像和进行染色模糊处理后的图像进行融合处理得到荧光图像（S205）；使投影模块（21）向投影区域投影荧光图像（S206）。通过上述方式，能够实现投影模块（21）投影荧光图像，荧光图像能够与环境光区分开来，方便用户观看荧光图像，另外还能够根据投影模块（21）的投影区域的环境光的光照强度，调节荧光图像的荧光化程度，使得荧光图像更加符合投影环境的需要。

Description

一种投影仪图像荧光处理的方法及系统 技术领域
本发明涉及投影技术领域，特别是涉及一种投影仪图像荧光处理的方法及系统。
背景技术
投影仪(又称投影机)，是一种可以将图像或视频投射到幕布上的设备，其投影到幕布上的图像或者视频在保持清晰度的情况下呈现数倍或者数十倍进行放大，方便人们观看，也给予人们开阔的视野，因此，投影仪深受用户的欢迎。
由于投影仪是将图像或视频直接投射到幕布，幕布上所显示的投影图像的投影效果会受幕布所在的区域的环境光的影响，若环境光过强时，环境光会盖过投影仪出射的投影光，使得幕布呈视泛白的效果，用户无法观看到投影画面，若环境光过弱，则幕布显示的投影画面过暗，会容易使人们无法清楚获取投影图像所反映的信息。
发明内容
本发明主要解决的技术问题是提供一种投影仪图像荧光处理的方法及系统，能够实现投影模块投影荧光图像，其中，荧光图像能够与环境光区分开来，方便用户观看荧光图像，并且能够根据投影模块的投影区域的环境光的环境光的光照强度，调节荧光图像的荧光化程度，使得荧光图像更加符合投影环境的需要。
为解决上述技术问题，本发明采用的一个技术方案是：提供一种投影仪图像荧光处理的方法，包括获取投影图像；对所述投影图像进行灰度处理，得到灰度图像；从所述灰度图像，提取轮廓图像，并对所述轮廓图像进行腐蚀膨胀处理；检测所述投影模块进行投影的投影区域的环 境光的光照强度，并根据所述环境光的光照强度对腐蚀膨胀处理后的图像进行染色模糊处理；将所述轮廓图像和进行染色模糊处理后的图像进行融合处理得到荧光图像；使所述投影模块向所述投影区域投影所述荧光图像。
其中，对所述投影图像进行灰度处理，得到灰度图像的步骤包括：获取所述投影图像的像素点的RGB值；根据所述投影图像的像素点的RGB值，计算灰度值；将所述投影图像的像素点的RGB值置换为所述灰度值，得到所述灰度图像。
其中，根据所述像素点的RGB值，计算所述像素点的灰度值的计算公式为：
Gray＝α*R+β*G+γ*B
所述Gray为灰度值，所述R为所述像素点的RGB值中红色分量的颜色值，所述G为所述像素点的RGB值中绿色分量的颜色值,所述B为所述像素点的RGB值中蓝色分量的颜色值，所述α为大于0.2并且小于0.4的数值，所述β为大于0.5并且小于0.7的数值，所述γ为大小0.1并且小于0.3的数值。
其中，所述根据所述环境光的光照强度对腐蚀膨胀处理后的图像进行染色模糊处理的步骤包括：对所述腐蚀膨胀处理后的图像先进行染色处理；根据所述环境光的光照强度选择高斯模糊处理的矩阵模板，所述高斯模糊处理的矩阵模板与环境光的光照强度之间具有预定的正相关关系；将所述染色后的图像与所选择的高斯模糊处理的矩阵模板进行卷积运算，得到所述染色模糊处理后的图像。
其中，所述对所述轮廓图像进行腐蚀膨胀处理的步骤包括：提取所述轮廓图像内各个物体的轮廓边缘；消除所述轮廓边缘的毛刺，并扩大所述轮廓边缘，以及填补所述轮廓图像内各个物体内部的空白部分。
为解决上述技术问题，本发明采用的另一个技术方案是：提供一种投影荧光图像的系统，包括投影模块、光检测装置和处理器，所述处理器分别与投影模块和光检测装置连接；所述处理器用于：获取投影图像；对所述投影图像进行灰度处理，得到灰度图像；从所述灰度图像，提取 轮廓图像，并对所述轮廓图像进行腐蚀膨胀处理；通过所述光检测装置检测所述投影模块进行投影的投影区域的环境光的光照强度，并根据所述环境光的光照强度对腐蚀膨胀处理后的图像进行染色模糊处理；将所述轮廓图像和进行染色模糊处理后的图像进行融合处理得到荧光图像；向所述投影模块发送所述荧光图像，并使所述投影模块向所述投影区域投影所述荧光图像。
其中，所述处理器对所述投影图像进行灰度处理，得到灰度图像的步骤包括：获取所述投影图像的像素点的RGB值；根据所述投影图像的像素点的RGB值，计算灰度值；将所述投影图像的像素点的RGB值置换为所述灰度值，得到所述灰度图像。
其中，根据所述像素点的RGB值，计算所述像素点的灰度值的计算公式为：
Gray＝α*R+β*G+γ*B
所述Gray为灰度值，所述R为所述像素点的RGB值中红色分量的颜色值，所述G为所述像素点的RGB值中绿色分量的颜色值,所述B为所述像素点的RGB值中蓝色分量的颜色值，所述α为大于0.2并且小于0.4的数值，所述β为大于0.5并且小于0.7的数值，所述γ为大小0.1并且小于0.3的数值。
其中，所述处理器根据所述环境光的光照强度对腐蚀膨胀处理后的图像进行染色模糊处理的步骤包括：对所述腐蚀膨胀处理后的图像进行染色处理；根据所述环境光的光照强度选择高斯模糊处理的矩阵模板，所述高斯模糊处理的矩阵模板与环境光的光照强度之间具有预定的正相关关系；将所述染色后的图像与所选择的高斯模糊处理的矩阵模板进行卷积运算，得到所述染色模糊处理后的图像。
其中所述处理器对所述轮廓图像进行腐蚀膨胀处理的步骤包括：提取所述轮廓图像内各个物体的轮廓边缘；消除所述轮廓边缘的毛刺，并扩大所述轮廓边缘，以及填补所述轮廓图像内各个物体内部的空白部分。
本发明的有益效果是：区别于现有技术的情况，本发明在获取到投 影图像后，依次对投影图像进行投影图像进行灰度处理，得到灰度图像；从灰度图像，提取轮廓图像，并对轮廓图像进行腐蚀膨胀处理；对腐蚀膨胀处理后的图像进行染色模糊处理，最后将轮廓图像和进行染色模糊处理后的图像进行融合处理得到荧光图像，使投影模块发送荧光图像，实现投影荧光图像，，其中，荧光图像能够与环境光区分开来，方便用户观看荧光图像；进一步的，在对腐蚀膨胀处理后的图像进行染色模糊处理时，是投影区域的环境光的光照强度进行的，具体为环境光的光照强度越强，模糊处理的程度越深，图像荧光化越强，环境光的光照强度越弱，模糊处理的程度越浅，图像荧光化越弱，使得荧光图像更加符合投影环境的需要。
附图说明
图1是本发明投影荧光图像的系统实施方式的示意图；
图2是本发明投影仪图像荧光处理的方法实施方式的流程图；
图3是本发明投影仪图像荧光处理的方法实施方式中生成灰度图像的流程图；
图4是本发明投影仪图像荧光处理的方法实施方式对图像进行染色模糊处理的流程图。
具体实施方式
下面结合附图和实施方式对本发明进行详细说明。
请参阅图1，投影荧光图像的系统20包括投影模块21、光检测装置22和处理器23，处理器23分别与投影模块21和光检测装置22连接。光检测装置22用于检测投影模块21的投影区域的环境光的光照强度。环境光的光照强度是指在单位面积上所接受可见光的能量。除了通过光检测装置22直接检测投影区域的环境光的光照强度之外，也可以利用带有采集功能的镜头装置拍摄一幅投影环境图像，再对该图像进行灰度处理，通过计算灰度图像的每个像素点的灰度值得出图片的环境光的光照强度，即为投影环境中的环境光的光照强度，当然，本领域技术人员 也可以采用其它方法检测投影区域的环境光的光照强度，此处不再一一赘述。
处理器23用于：获取投影图像；对投影图像进行灰度处理，得到灰度图像，从灰度图像，提取轮廓图像，并对轮廓图像进行腐蚀膨胀处理，通过光检测装置22检测投影模块21进行投影的投影区域的环境光的光照强度，并根据环境光的光照强度对腐蚀膨胀处理后的图像进行染色模糊处理，将轮廓图像和进行染色模糊处理后的图像进行融合处理得到荧光图像，向投影模块21发送荧光图像，并使投影模块21向投影区域投影荧光图像。
值得说明的是：在提取得到的轮廓图像后，会保存轮廓图像的副本，其中，轮廓图像的副本与原轮廓图像相同，后将轮廓图像和进行染色模糊处理后的图像进行融合处理具体为：将轮廓图像的副本与进行染色模糊处理后的图像进行融合处理。
灰度图像是指在黑色与白色之间还有许多级的颜色深度的图像，R、G、B分别为投影图像每个像素点的红色分量、绿色分量、蓝色分量三个的颜色值。投影图像中的每个像素的颜色有R、G、B三个分量决定，而每个分量有255中值可取，这样一个像素点可以有1600多万(255*255*255)的颜色的变化范围。而灰度图像是R、G、B三个分量相同的一种特殊的彩色图像，其一个像素点的变化范围为255种，灰度处理即将图像的颜色由多变的彩色变化范围缩小到黑与白之间的变化范围，则处理器23对投影图像进行灰度处理，得到灰度图像的步骤包括：获取投影图像的像素点的RGB值，根据投影图像的像素点的RGB值，计算灰度值，将投影图像的像素点的RGB值置换为灰度值，得到灰度图像，其中，计算像素点的灰度值的计算公式为：
Gray＝α*R+β*G+γ*B
Gray为灰度值，R为像素点的RGB值中红色分量的颜色值，G为像素点的RGB值中绿色分量的颜色值,B为像素点的RGB值中蓝色分量的颜色值，α为大于0.2并且小于0.4的数值，β为大于0.5并且小于0.7的数值，γ为大小0.1并且小于0.3的数值。。当然，上述只是说明其中 一种较优的将投影图像转换为灰度图像的方法，本领域技术人员也可以采用其它方法将投影图像转换灰度图像。
轮廓图像是指能够体现投影图像中各个物体的轮廓的图像，处理器23对轮廓图像进行腐蚀膨胀处理的步骤具体包括提取轮廓图像内各个物体的轮廓边缘；消除轮廓边缘的毛刺，并扩大轮廓边缘，以及填补轮廓图像内各个物体内部的空隙。具体而言，在消除轮廓边缘的毛刺后，扩大各个物体的轮廓，然后填充轮廓图像内各个物体内部的空白部分。通过上述处理，图轮廓图像变得更加平滑，从而减少轮廓图像中的具体细节的要求。
对图像进行模糊处理时，是根据环境光的光照强度进行，具体的，环境光的光照强度越强，模糊处理越深，环境光的光照强度越弱，模糊处理越浅，则处理器23根据环境光的光照强度对腐蚀膨胀处理后的图像进行染色模糊处理的步骤包括：对腐蚀膨胀处理后的图像进行染色处理，根据环境光的光照强度选择高斯模糊处理的矩阵模板，高斯模糊处理的矩阵模板与环境光的光照强度之间具有预定的正相关关系，将染色后的图像与所选择的高斯模糊处理的矩阵模板进行卷积运算，得到染色模糊处理后的图像。高斯模糊处理的矩阵模板与环境光的光照强度之间具有预定的正相关关系是指：环境光的光照强度越强，所选定的高斯模糊处理的矩阵模板越大，而高斯模糊处理的矩阵模板越大，则对图像进行模糊处理的程序越大，环境光的光照强度越弱，所选定的高斯模糊处理的矩阵模板越小，而高斯模糊处理的矩阵模板越小，则对图像进行模糊的程序越小；当然，高斯模糊处理的矩阵模板的大小与环境光的光照强度之间的预定的正相关关系可以根据实际情况设定。
进一步的，处理器23在将轮廓图像和进行染色模糊处理后的图像进行融合处理得到荧光图像中是以轮廓图像作为图像的前景，染色模糊处理后图像作为图像的背景，其中，染色模糊处理后的图像是一个比较模糊的图像，能够跟轮廓图像形成反衬，从而使得融合后的图像荧光化显示更加突出，投影出来的效果更佳。
当然，在得到荧光图像之后，在投影荧光图像之前，还可以对荧光 图像进行优化处理，例如：对荧光图像进行平滑处理，提高荧光图像的质量等等。
在本发明实施方式中，在获取到投影图像后，依次对投影图像进行投影图像进行灰度处理，得到灰度图像；从灰度图像，提取轮廓图像，并对轮廓图像进行腐蚀膨胀处理；对腐蚀膨胀处理后的图像进行染色模糊处理，最后将轮廓图像和进行染色模糊处理后的图像进行融合处理得到荧光图像，使投影模块发送荧光图像，实现投影荧光图像，其中，荧光图像能够与环境光区分开来，方便用户观看荧光图像；进一步的，在对腐蚀膨胀处理后的图像进行染色模糊处理时，是投影区域的环境光的光照强度进行的，具体为环境光的光照强度越强，模糊处理的程度越深，图像荧光化越强，环境光的光照强度越弱，模糊处理的程度越浅，图像荧光化越弱，使得荧光图像更加符合投影环境的需要。
本发明又提供投影仪图像荧光处理的方法实施方式。请参阅图2，方法包括:
步骤S201：获取投影图像；
投影图像是由外部设备提供的，也可以从系统内部的存储器上提取得到的。
步骤S202：对投影图像进行灰度处理，得到灰度图像；
灰度图像是指只有黑白两种颜色的图像，其能够使观看者可以更直观地区分出图像内各物体的形状和轮廓。投影图像每个像素点的RGB值包括R值、G值和B值，投影图像中的每个像素的颜色有R、G、B三个颜色分量决定，而每个颜色分量有255中值可取，这样一个像素点可以有1600多万(255*255*255)的颜色的变化范围。而灰度图像是R、G、B三个分量相同的一种特殊的彩色图像，其一个像素点的变化范围为255种，灰度处理即将图像的颜色由多变的彩色变化范围缩小到黑与白之间的变化范围。而将投影图像转换为恢复就是为改变投影图像内各个像素点的RGB值，使投影图像只有黑白两种颜色，则如图3所示，步骤S202包括：
步骤S2021：获取投影图像的像素点的RGB值；
步骤S2022：根据投影图像的像素点的RGB值，计算灰度值，其中，计算像素点的灰度值的计算公式为：
Gray＝α*R+β*G+γ*B
Gray为灰度值，R为像素点的RGB值中红色分量的颜色值，G为像素点的RGB值中绿色分量的颜色值,B为像素点的RGB值中蓝色分量的颜色值，α为大于0.2并且小于0.4的数值，β为大于0.5并且小于0.7的数值，γ为大小0.1并且小于0.3的数值。
步骤S2023：将投影图像的像素点的RGB值置换为灰度值，得到灰度图像。
步骤S203：从灰度图像，提取轮廓图像，并对轮廓图像进行腐蚀膨胀处理；
值得说明的是：在提取得到轮廓图像后，保存轮廓图像的副本，以方便后续进行处理。
而对轮廓图像进行腐蚀膨胀处理是为使轮廓图像内各个物体的轮廓更加清晰，具体的步骤S203包括：提取轮廓图像内各个物体的轮廓边缘，消除轮廓边缘的毛刺，并扩大轮廓边缘，以及填补轮廓图像内各个物体内部的空白部。对轮廓图像进行腐蚀膨胀处理后，图像更加平滑，从而能够减少图像中的一些细节。
步骤S204：检测投影模块进行投影的投影区域的环境光的光照强度，并根据环境光的光照强度对腐蚀膨胀处理后的图像进行染色模糊处理；
投影区域是指投影模块进行投影时投影画面所在区域。在对图像进行模糊处理时，环境光的光照强度越强，模糊处理越深，环境光的光照强度越弱，模糊处理越浅，以使荧光图像更加符合投影环境的需要，则如图4所示，步骤S204又包括：
步骤S2041：根据环境光的光照强度选择高斯模糊处理的矩阵模板，高斯模糊处理的矩阵模板与环境光的光照强度之间具有预定的正相关关系；
高斯模糊处理的矩阵模板与环境光的光照强度之间具有预定的正 相关关系是指：环境光的光照强度越强，所选定的高斯模糊处理的矩阵模板越大，而高斯模糊处理的矩阵模板越大，则对图像进行模糊处理的程序越大，环境光的光照强度越弱，所选定的高斯模糊处理的矩阵模板越小，而高斯模糊处理的矩阵模板越小，则对图像进行模糊的程序越小；当然，高斯模糊处理的矩阵模板的大小与环境光的光照强度之间的预定的正相关关系可以根据实际情况设定。
步骤S2042：将染色后的图像与所选择的高斯模糊处理的矩阵模板进行卷积运算，得到染色模糊处理后的图像。
步骤S205：将轮廓图像和进行染色模糊处理后的图像进行融合处理得到荧光图像；
将轮廓图像和进行染色模糊处理后的图像进行融合处理得到荧光图像中是指以轮廓图像作为图像的前景，染色模糊处理后图像作为图像的背景，其中，染色模糊处理后的图像是一个比较模糊的图像，能够跟轮廓图像形成反衬，从而使得融合后的图像荧光化显示更加突出，投影出来的效果更佳。
步骤S206：使投影模块向投影区域投影荧光图像。
当然，在得到荧光图像之后，在投影荧光图像之前，还可以对荧光图像进行优化处理，例如：对荧光图像进行平滑处理，提高荧光图像的质量等等。
在本发明实施方式中，在获取到投影图像后，依次对投影图像进行投影图像进行灰度处理，得到灰度图像；从灰度图像，提取轮廓图像，并对轮廓图像进行腐蚀膨胀处理；对腐蚀膨胀处理后的图像进行染色模糊处理，最后将轮廓图像和进行染色模糊处理后的图像进行融合处理得到荧光图像，使投影模块发送荧光图像，实现投影荧光图像，其中，荧光图像能够与环境光区分开来，方便用户观看荧光图像；进一步的，在对腐蚀膨胀处理后的图像进行染色模糊处理时，是投影区域的环境光的光照强度进行的，具体为环境光的光照强度越强，模糊处理的程度越深，图像荧光化越强，环境光的光照强度越弱，模糊处理的程度越浅，图像荧光化越弱，使得荧光图像更加符合投影环境的需要。
以上所述仅为本发明的实施方式，并非因此限制本发明的专利范围，凡是利用本发明说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本发明的专利保护范围内。

Claims (10)

  1. 一种投影仪图像荧光处理的方法，其特征在于，包括：
    获取投影图像；
    对所述投影图像进行灰度处理，得到灰度图像；
    从所述灰度图像，提取轮廓图像，并对所述轮廓图像进行腐蚀膨胀处理；
    检测投影模块进行投影的投影区域的环境光的光照强度，并根据所述环境光的光照强度对腐蚀膨胀处理后的图像进行染色模糊处理；
    将所述轮廓图像和进行染色模糊处理后的图像进行融合处理得到荧光图像；
    使所述投影模块向所述投影区域投影所述荧光图像。
  2. 根据权利要求1所述的方法，其特征在于，
    对所述投影图像进行灰度处理，得到灰度图像的步骤包括：
    获取所述投影图像的像素点的RGB值；
    根据所述投影图像的像素点的RGB值，计算灰度值；
    将所述投影图像的像素点的RGB值置换为所述灰度值，得到所述灰度图像。
  3. 根据权利要求1所述的方法，其特征在于，
    根据所述像素点的RGB值，计算所述像素点的灰度值的计算公式为：
    Gray＝α*R+β*G+γ*B
    所述Gray为灰度值，所述R为所述像素点的RGB值中红色分量的颜色值，所述G为所述像素点的RGB值中绿色分量的颜色值,所述B为所述像素点的RGB值中蓝色分量的颜色会上，所述α为大于0.2并且小于0.4的数值，所述β为大于0.5并且小于0.7的数值，所述γ为大小0.1并且小于0.3的数值。
  4. 根据权利要求1所述的方法，其特征在于，
    所述根据所述环境光的光照强度对腐蚀膨胀处理后的图像进行染色模糊处理的步骤包括：
    对所述腐蚀膨胀处理后的图像先进行染色处理；
    根据所述环境光的光照强度选择高斯模糊处理的矩阵模板，所述高斯模糊处理的矩阵模板与环境光的光照强度之间具有预定的正相关关系；
    将所述染色后的图像与所选择的高斯模糊处理的矩阵模板进行卷积运算，得到所述染色模糊处理后的图像。
  5. 根据权利要求1所述的方法，其特征在于，
    所述对所述轮廓图像进行腐蚀膨胀处理的步骤包括：
    提取所述轮廓图像内各个物体的轮廓边缘；
    消除所述轮廓边缘的毛刺，并扩大所述轮廓边缘，以及填补所述轮廓图像内各个物体内部的空白部分。
  6. 一种投影荧光图像的系统，包括投影模块、光检测装置和处理器，所述处理器分别与投影模块和光检测装置连接；
    所述处理器用于：
    获取投影图像；
    对所述投影图像进行灰度处理，得到灰度图像；
    从所述灰度图像，提取轮廓图像，并对所述轮廓图像进行腐蚀膨胀处理；
    通过所述光检测装置检测所述投影模块进行投影的投影区域的环境光的光照强度，并根据所述环境光的光照强度对腐蚀膨胀处理后的图像进行染色模糊处理；
    将所述轮廓图像和进行染色模糊处理后的图像进行融合处理得到荧光图像；
    向所述投影模块发送所述荧光图像，并使所述投影模块向所述投影区域投影所述荧光图像。
  7. 根据权利要求6所述的系统，其特征在于，
    所述处理器对所述投影图像进行灰度处理，得到灰度图像的步骤包括：
    获取所述投影图像的像素点的RGB值；
    根据所述投影图像的像素点的RGB值，计算灰度值；
    将所述投影图像的像素点的RGB值置换为所述灰度值，得到所述灰度图像。
  8. 根据权利要求7所述的系统，其特征在于，
    根据所述像素点的RGB值，计算所述像素点的灰度值的计算公式为：
    Gray＝α*R+β*G+γ*B
    所述Gray为灰度值，所述R为所述像素点的RGB值中红色分量的颜色值，所述G为所述像素点的RGB值中绿色分量的颜色值,所述B为所述像素点的RGB值中蓝色分量的颜色值，所述α为大于0.2并且小于0.4的数值，所述β为大于0.5并且小于0.7的数值，所述γ为大小0.1并且小于0.3的数值。
  9. 根据权利要求6所述的系统，其特征在于，
    所述处理器根据所述环境光的光照强度对腐蚀膨胀处理后的图像进行染色模糊处理的步骤包括：
    对所述腐蚀膨胀处理后的图像进行染色处理；
    根据所述环境光的光照强度选择高斯模糊处理的矩阵模板，所述高斯模糊处理的矩阵模板与环境光的光照强度之间具有预定的正相关关系；
    将所述染色后的图像与所选择的高斯模糊处理的矩阵模板进行卷积运算，得到所述染色模糊处理后的图像。
  10. 根据权利要求6所述的系统，其特征在于，
    所述处理器对所述轮廓图像进行腐蚀膨胀处理的步骤包括：
    提取所述轮廓图像内各个物体的轮廓边缘；
    消除所述轮廓边缘的毛刺，并扩大所述轮廓边缘，以及填补所述轮廓图像内各个物体内部的空白部分。
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110689926A (zh) * 2018-06-19 2020-01-14 上海交通大学 一种高通量数字pcr图像液滴的准确检测方法
CN110909747A (zh) * 2019-05-13 2020-03-24 河南理工大学 一种基于多颜色空间主元分析描述的煤矸石识别方法
CN111489322A (zh) * 2020-04-09 2020-08-04 广州光锥元信息科技有限公司 给静态图片加天空滤镜的方法及装置

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105472361B (zh) * 2015-11-19 2018-03-27 广景视睿科技（深圳）有限公司 一种投影仪图像荧光处理的方法及系统
CN108174170B (zh) * 2017-12-29 2020-03-17 安徽慧视金瞳科技有限公司 基于摄像头的投影区域尺寸自检测方法、系统及设备
CN109410236B (zh) * 2018-06-12 2021-11-30 佛山市顺德区中山大学研究院 荧光染色图像反光点识别与重定义的方法及系统

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007281893A (ja) * 2006-04-06 2007-10-25 Olympus Corp プロジェクタシステム
CN101217674A (zh) * 2007-01-04 2008-07-09 三星电子株式会社 用于环境光自适应颜色校正的设备和方法
WO2013038656A1 (ja) * 2011-09-15 2013-03-21 日本電気株式会社 投影像自動補正システム、投影像自動補正方法およびプログラム
CN103729829A (zh) * 2013-12-13 2014-04-16 深圳市云宙多媒体技术有限公司 一种彩色图像抽线的渲染方法及装置
CN104063848A (zh) * 2014-06-19 2014-09-24 中安消技术有限公司 一种低照度图像增强方法和装置
US20140285532A1 (en) * 2013-03-22 2014-09-25 Delta Electronics, Inc. Projection sysyem, projector, and calibration method thereof
CN105472361A (zh) * 2015-11-19 2016-04-06 广景视睿科技（深圳）有限公司 一种投影仪图像荧光处理的方法及系统

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP3719411B2 (ja) * 2001-05-31 2005-11-24 セイコーエプソン株式会社 画像表示システム、プロジェクタ、プログラム、情報記憶媒体および画像処理方法
JP2007166271A (ja) * 2005-12-14 2007-06-28 Seiko Epson Corp プロジェクションシステムおよびプロジェクタ
CN101860761B (zh) * 2010-04-16 2012-09-05 浙江大学 投影显示图像颜色失真校正方法
CN101917631B (zh) * 2010-07-30 2012-04-25 浙江大学 一种在日常照明环境下的投影显示颜色再现方法
CN103942813A (zh) * 2014-03-21 2014-07-23 杭州电子科技大学 一种电动轮椅运动下的单运动目标实时检测方法
CN104463858A (zh) * 2014-11-28 2015-03-25 中国航空无线电电子研究所 一种投影颜色自适应校正方法

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007281893A (ja) * 2006-04-06 2007-10-25 Olympus Corp プロジェクタシステム
CN101217674A (zh) * 2007-01-04 2008-07-09 三星电子株式会社 用于环境光自适应颜色校正的设备和方法
WO2013038656A1 (ja) * 2011-09-15 2013-03-21 日本電気株式会社 投影像自動補正システム、投影像自動補正方法およびプログラム
US20140285532A1 (en) * 2013-03-22 2014-09-25 Delta Electronics, Inc. Projection sysyem, projector, and calibration method thereof
CN103729829A (zh) * 2013-12-13 2014-04-16 深圳市云宙多媒体技术有限公司 一种彩色图像抽线的渲染方法及装置
CN104063848A (zh) * 2014-06-19 2014-09-24 中安消技术有限公司 一种低照度图像增强方法和装置
CN105472361A (zh) * 2015-11-19 2016-04-06 广景视睿科技（深圳）有限公司 一种投影仪图像荧光处理的方法及系统

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110689926A (zh) * 2018-06-19 2020-01-14 上海交通大学 一种高通量数字pcr图像液滴的准确检测方法
CN110909747A (zh) * 2019-05-13 2020-03-24 河南理工大学 一种基于多颜色空间主元分析描述的煤矸石识别方法
CN110909747B (zh) * 2019-05-13 2023-04-07 河南理工大学 一种基于多颜色空间主元分析描述的煤矸石识别方法
CN111489322A (zh) * 2020-04-09 2020-08-04 广州光锥元信息科技有限公司 给静态图片加天空滤镜的方法及装置

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