Method for intelligently adjusting endoscope illuminance

Abstract

The invention discloses a method for intelligently adjusting the endoscope illuminance, which comprises the following steps of: step 1, initializing; step 2, outputting standard illuminance by a cold light source of an endoscope; step 3, when the endoscope is in a working state, observing and acquiring the interior real-time image of a human organ; step 4, respectively obtaining the pixel values R1(u, v), G1(u, v), B1(u, v) and the average values bar(R)1(u, v), bar(G)1(u, v), bar(B)1(u, v) of the pixel values of the R, G and B three primary colors of an RGB real-time color image; step 5, carrying out color cast correction on the real-timely acquired image; step 6, selecting the maximum and minimum from the pixel values of the three primary colors after the color cast correction; step 7, correcting the image brightness; step 8, calculating the image pixel average value after the image brightness correction and the comprehensive average value thereof; and step 10, comparing J and J0 in the database, and adjusting the illuminance output of the cold light source. According to the method, the endoscope illuminance can be intelligently adjusted to realize an optimized effect no matter how the endoscope is bent.

Description

technical field [0001] The invention relates to a method in the technical field of automatic control of medical equipment, in particular to an intelligent adjustment method for endoscope illumination. Background technique [0002] In recent years, medical endoscope systems have been widely used in clinical medicine. Medical endoscope is a miniature camera system that can put the camera into the human body. Under the illumination of its own light source, the observed target is imaged on the target surface of the image sensor through the optical system, and the optical signal is converted into an electrical signal. After magnification and image processing, a clear magnified image is displayed on the monitor. With the assistance of the endoscope system, doctors can better discover the lesions that occur on the soft and hard tissues in the human body, and allow patients to intuitively and comprehensively understand various problems in their own bodies. These images can also be...

AI Technical Summary

Problems solved by technology

However, the biggest disadvantage of this algorithm is that it is necessary to "put the reference plate (supervisory color plate) with three colors of red, green, and blue into the field of view, and collect it simultaneously with the image to be recognized". The color cast feature of the entire image can be obtained by analyzing the board image. Under standard light source conditions, the gains of the three channels are adjusted separately.

Obviously, the algorithm provided by this document is relatively cumbersome and complicated, and it cannot be applied to the configuration of the extremely narrow endoscope illumination in the working space, and it does not have the function of automatic adjustment of illumination

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