Introduction to the imaging function of stereomicroscope
The stereomicroscope system is an optical imaging system composed of a metallographic microscope and a macroscopic camera stage, which is used to form images of metallographic specimens or photographs. Stereoscopic microscopy can directly perform quantitative metallographic analysis on metallographic samples; The macro camera station is suitable for analyzing metallographic photos, negatives, and physical objects.
In order to store, process, and analyze images using a computer, it is first necessary to digitize the images. A frame of image is composed of a distribution of different grayscales, represented by mathematical symbols as j=j (x, y), where x and y are the coordinates of pixels on the image, and j represents their grayscale values.
So, a frame of image can be represented by an m x n-th moment, where each element corresponds to a pixel in the image, and the value of aij represents the grayscale value of the pixel in the i-th row and j-th column of the image. CCD camera (charge coupled device camera) is an image digitization device. The stereo microscope features on the metallographic sample are imaged on CCD after being processed by an optical system, and then converted and scanned by CCD. They are then taken out as image signals, amplified by amplifiers, quantified into grayscale levels, and stored to obtain digital images. The computer sets the grayscale threshold T based on the grayscale range of the features to be measured in the digital image.
For any pixel in a digital image, if its grayscale is greater than or equal to T, use white (grayscale value 255) to replace its original grayscale; If it is less than T, black (grayscale value 0) is used to replace the original grayscale. A stereo microscope can convert grayscale images into binary images with only black and white grayscales, and then perform necessary processing on the images, making it convenient for computers to perform image analysis work on binary images such as particle counting, area measurement, and perimeter measurement. If pseudocolor processing is used, 256 grayscale levels can be converted into corresponding colors, making details with close grayscale levels and their surrounding environment or other details easy to recognize, thereby improving the image and facilitating computer processing of multi feature images.
