There are several ways to access the data in a RasterImage. If you need to get the RGB values of each pixel, then the GetPixel() and GetRow() methods are the simplest methods to use.

Few Pixels

If you need to get just one pixel, then GetPixel() is the easiest. GetPixel() works with image data of any bits per pixel and returns a RasterColor that includes the alpha channel information for 32 and 64 bit images. The sample below uses GetPixel()to fill the buffer with the entire image (not recommended—more on that below).

Digital number recognition from LCD displays can be a challenge when it comes to recognizing seven-segment or dot-matrix displays. This is because the lines in the numbers do not actually connect when forming the number. When performing OCR on images that contain these fonts, you will need to do some image processing to increase the accuracy. This can easily be done with two functions from the LEADTOOLS Image Processing SDK that is included with LEADTOOLS Recognition and Document Imaging products.

I recently became intrigued by some art work I saw online. It is a bunch of Rubik's cubes set up to reproduce a picture.

The artists are essentially reducing the image's colors down to a palette of six colors with dithering. By dithering the picture, it appears to look like the subject from a distance because the colors mix and merge to resemble the original colors. But the closer you get to the piece, the more it appears to be a bunch of randomly ordered colored squares. It sparked the artist in me, so I decided to use LEADTOOLS to help me come up with my own Rubik's Cubism-like art.

Tonal range is an important attribute of an image, especially photographs, when trying to improve OCR results. Tonal range is the range of tones between the lightest and darkest areas of an image and is also known as contrast. An image with a wide range has both very dark (black) and very light (white) elements. An image with a narrow range is more limited in its tonal scope, which is usually in the mid-ranges (varying shades of grays).

Recently, a customer needed to find the differences between two images. More specifically the customer needed to find what changed between the two images and crop to leave only the change. From there, the LEADTOOLS OCR engine converted the cropped image to text to create a screen reader for visually impaired users. Additionally, animation and compression algorithms use similar techniques to improve performance and efficiency.

Support quickly responded to the customer with a C# console application example that finds the bounding rectangle of the differences and then crops the image.