In our image vectorization process, color quantization plays a significant role because it reduces the number of used colors that significantly affect the size and quality of vectorized SVG. It is a process that reduces the number of different colors used in an image, with the intention that the new image should be as visually similar as possible to the original image. Color quantization or color image quantization is quantization applied to color spaces. The image vectorization process includes the next steps:Ĭolor quantization and resizing.
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Vectorization can be used to update or recover images. Vectorized images are more resistant to such attacks because image recognizers are usually pixel-oriented.
Sometimes it is necessary to protect images from image recognition techniques like face recognition. In other words, vector graphics have a unique advantage over raster graphics in that points, lines, and curves can be scaled up or down to any resolution without aliasing. Unlike bitmap graphics, vector images are resizable and scalable without losing any quality, and they will still display out just as clearly. This is because pixels are stretched over a larger area, making them less sharp. For example, scaling a bitmap to enlarge it without changing the resolution will lose quality and appear blurry or pixelated. Therefore, the more pixels in the image and the higher the resolution, the higher the image quality. The image quality depends on the number of pixels that make up the image and the value of resolution that determines how many pixels are displayed per inch. Raster images are pixel-based, so they are resolution-dependent. These images are based on geometric shapes and drawn with simple curves. Images such as maps, icons, logos, technical drawings and clip art are suitable for vectorization. The output image is a vector file format, for example, SVG file format. The source image to the raster-to-vector conversion may accept bitmap formats such as JPG, TIFF, BMP, GIF and PNG. Image Vectorization is the process of converting raster images into vector graphics - the Bezier curves, splines and lines. Each pixel is a triplet of 8-bit integer values, where each value represents an amount of red, green, and blue color.
If it is an RGB image, it can be represented as a table of color pixels. Such vector images are defined as Cartesian points connected by lines and curves to form required shapes. The two-dimensional vector graphics are computer graphics images represented as mathematical curves. The task in vectorization is to convert a 2D image to a 2D vector representation of the image.
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