Color rendering refers to the objective effect produced by light emitted by a light source on an object and the degree of appearance of the true color of the object, which is an important indicator of the illumination light source. The light source with high color rendering performs better on the color, the color seen is close to the natural color, and the light source with low color rendering performs poorly on the color, and the color deviation seen is also large. If the light emitted by the light source contains a proportion of each color of light that is similar to natural light, the colors seen by the human eye are more realistic. The spectral distribution of the light source determines the color rendering of the light source. The color rendering of the light source affects the color of the object observed by the human eye. Quantitative evaluation of the color rendering property of the light source is an important indicator for evaluating the quality of the light source. General artificial lighting sources use the general color rendering index as an evaluation index of color rendering, and the color rendering index is also an important parameter to measure the color characteristics of the light source. According to different application fields, Nanjing Hecho Technology Co., Ltd. launched a new ultra-bright high color rendering index medical Endoscope Light Source Module; ultra-high brightness LED Cold Light Source, and Fiber Optic Illuminators and other products to meet the needs of different customers, welcome The majority of new and old customers to inquire.

The core technologies of machine vision include image acquisition, image pre-processing, feature extraction, target detection and recognition, etc. First, machine vision needs to obtain the image through devices such as cameras, and then preprocess the image, including denoising, enhancement, geometric correction, etc., to eliminate the interference and noise in the image. Object detection and recognition is one of the important tasks of machine vision. By training models and using machine learning algorithms, machine vision can identify and locate target objects in the image, such as faces, vehicles, product defects, and so on. This provides very valuable applications for automated production, intelligent security and intelligent transportation. The development of machine vision technology benefits from the improvement of computer computing power, the improvement of sensor technology and the development of artificial intelligence technology such as deep learning. These advances have led to significant improvements in accuracy, real-time, and adaptability.