This is the simplest method, however, it gives you no control over the conversion. A grayscale image is one in which the only colors are shades of gray. Thus it is best to avoid your camera’s built-in B&W mode and try these post-production techniques instead: While most digital cameras have a B&W mode, which turns your image to black and white as you shoot, it can also leave your photos looking flat and washed out. This will leave you with a lot more information to work with and higher-quality conversions. To get the best results during the editing stage, start by shooting in RAW format and outputting your images as 16-bit TIFF files. Quick ways to convert black and white images on Macĭigitally converting a colored image to black and white gives you the advantage of complete control over the outcome. Let’s look at some effortless ways to convert images to black and white, selectively change the colors within a photo, and even colorize your old family pictures. Whether you are a photographer who wants to try a new style, a blogger wishing to be on top of trends, or you simply want to create a vintage atmosphere in your photo albums, turning an image to black and white is a useful skill to master. Grayscale images in design are said to improve its composition, making it easier to get a message across to the audience. Black and white photos, portraits especially, are often considered more impactful, because the absence of color removes distractions and lets the viewer focus on the actions and emotions displayed. To learn more about imaging fundamentals, read the first article in the Image Processing 101 Series: What is an Image, Color Models.The world looks different in monochrome, allowing us to see tone, texture, and light in new ways. Otherwise, it is set to white (grayscale = 255). If the intensity level of a pixel is smaller than the threshold, the pixel is set to black (grayscale = 0). The basic idea is to find a point between the peak of the foreground pixel values and the peak of the background pixel values. Image histogram can be used to automatically determine the value of the threshold to be used for converting a grayscale image to a binary image. The image histogram is a statistical graph with grayscale value on the x-axis and the number of pixels for each grayscale on the y-axis.
The global thresholding method takes advantage of the image histogram. The image is divided into several sub-blocks, and the distribution of gray-value in each block was analyzed. With the local thresholding method, a threshold is calculated at each pixel, which depends on some local statistics such as mean, range, and the variance of the pixel neighborhood. The images below show an example of before and after binarization. Global thresholding - calculates the threshold once for all pixels.Local thresholding - calculates the threshold pixel by pixel.The critical task is to find a suitable threshold. This transformation is useful in detecting blobs and further reduces the computational complexity. Binarization: Grayscale to black/white Conversionīinarization converts a grayscale image to a black/white image. RGB_image = cv2.imread("thai-government-lottery.png")