UNITROL 1020 UNS0119A-Z,V1 3BHE030579R0003 | ABB module

Description

UNITROL 1020 UNS0119A-Z,V1 3BHE030579R0003 | ABB module

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Advantages of UNITOL 1020 UNS0119A-Z, V1 3BHE030579R0003: 1. Iterative threshold image segmentation has higher practicality and robustness compared to static threshold segmentation. 2. This method can effectively address image segmentation problems in situations such as changes in lighting and complex and diverse backgrounds. Disadvantage: For large-sized images, the computational speed of iterative threshold image segmentation may become one of its drawbacks.

1.3 Adaptive Threshold Image Segmentation

1.3.1 Conventional methods

The segmentation steps for UNITOL 1020 UNS0119A-Z, V1 3BHE030579R0003 are as follows:

1. Define a window of size N × N N × NN × N for the input grayscale image, and select a pixel in the center of the window as the core pixel for processing.

2. Calculate the local threshold based on the pixel information within the window, which can serve as the threshold for the current pixel. This threshold can be a statistical measure such as mean, median, pattern, etc.

3. Compare the processed pixels with the local threshold of the current pixel, set pixels greater than or equal to the threshold as white, and pixels less than the threshold as black, and segment a new binary image.

4. UNITOL 1020 UNS0119A-Z, V1 3BHE030579R0003 Move the window to other areas of the image and continue to perform Gaussian adaptive threshold segmentation on each area until all areas of the image are segmented into binary images.

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