OpenCV Python – How to convert a colored image to a binary image? (2024)

FAQs

OpenCV Python – How to convert a colored image to a binary image? ›

The process of converting a picture to binary is called binarization and it can be done in multiple ways. The first method uses a color quantization algorithm that finds the two dominant colors in a picture and by calculating the difference in hue, all pixels take one or the other color value (whichever is closest).

The process of converting a picture to binary is called binarization and it can be done in multiple ways. The first method uses a color quantization algorithm that finds the two dominant colors in a picture and by calculating the difference in hue, all pixels take one or the other color value (whichever is closest).

Image binarization with OpenCV: cv2.

You can binarize an image with cv2. threshold() . If type is set to cv2. THRESH_BINARY , any value greater than the threshold thresh is replaced with maxval and the other values are replaced with 0 .

Code Implementation with Library

For converting the image into a binary image, we can simply make use of the threshold() method available in the cv2 library. This method, irrespective of what the image is (grayscale or RGB) converts into binary. It takes 4 arguments in use.

Step 1: Import OpenCV. Step 2: Read the original image using imread(). Step 3: Convert to grayscale using cv2. cvtcolor() function.

Start by converting each of the three numbers into binary, using 8 bits for each. You should get: - red = 10010001, - green = 00110010, - blue = 01111011. Putting these values together gives 100100010011001001111011, which is the bit representation for the colour above.

As you might know, RGB is simply three 8-bit values for red, green and blue. CMYK is four 8-bit values. When you use Image. convert('RGB') it just converts each pixel to the triple 8-bit value.

With 8-bit data, we can assign the darkest point in an image to the number 00000000, and the brightest point in the image to 11111111. This produces 256 shades of gray between black and white.

What is binary image OpenCV? ›

To convert an image to binary using OpenCV, you can use the cv2. threshold() function. This function applies a threshold to a grayscale image, converting it to a binary image. The cv2. threshold() function in OpenCV is used to apply a threshold to a grayscale image, effectively converting it into a binary image.

The importance of Binary Image in image processing is: they allow to separate objects easily from the background. The segmentation allows to label each pixel as 'object' and 'background' and assign black and white colour accordingly.

OpenCV uses BGR image format. So, when we read an image using cv2. imread() it interprets in BGR format by default. We can use cvtColor() method to convert a BGR image to RGB and vice-versa.

Image Binarization is the conversion of document image into bi-level document image. Image pixels are separated into dual collection of pixels, i.e. black and white. The main goal of image binarization is the segmentation of document into foreground text and background.

To read a binary file in Python, first, we need to open it in binary mode ('”rb”'). We can use the 'open()' function to achieve this. To create a binary file in Python, You need to open the file in binary write mode ( wb ).

Binary Images are image which consists of two colours i.e. “Black” and “White”. The pixels have only two possible intensity values, '0' for 'Black' and either '1' or '255' for 'White'. The importance of Binary Image in image processing is: they allow to separate objects easily from the background.