This project falls within the scope of basic research applications in the field of Traditional Chinese Medicine (TCM) diagnostics. Facial diagnosis is one of the important contents of observation diagnosis studies, and facial diagnostic information contains a wealth of important clinical information. For example, according to the TCM theory that associates the five internal organs with the five colors, observing changes in the five colors of blue, red, yellow, white, and black on the face has extremely important value for diagnosing organ diseases and syndromes. However, traditional facial diagnosis relies mainly on the subjective judgment of doctors, lacks objective diagnostic standards and evidence, is difficult to replicate, and past research has not fundamentally broken through the bottleneck problem of 'standardized collection and objective diagnosis of facial diagnosis.' This project is guided by TCM theories and clinical practice, applies digital image processing and pattern recognition technology to collect, analyze, and recognize facial diagnostic information, establishes standardized collection and digital diagnostic methods that conform to the characteristics of TCM diagnosis, and transforms this method into an intelligent diagnostic system. Applied in clinical objective diagnosis and efficacy evaluation, it has achieved multiple innovative results over the past decade: (1) Established standardized collection environment conditions and methods for TCM facial diagnosis images. Through the screening and determination of light sources, light guide materials, and CCD equipment, as well as the design of light paths, a portable facial diagnosis collection device with LED lighting was developed, achieving standardized collection of TCM facial diagnosis information. After comparative experiments under natural light and the conditions of the facial diagnosis collection device's light source by TCM experts, the consistency of facial diagnosis information observed under both conditions was very good, reaching over 90%, indicating that the established method has well achieved the true restoration of facial diagnosis images. (2) Proposed a quantitative classification method for the five colors in TCM facial diagnosis. Based on statistical analysis of TCM facial diagnosis literature, combined with the principles of observing colors and after repeated deliberation by experts, a clinical grading interpretation scale for TCM facial diagnosis was formulated. The scale was subjected to validity and reliability tests, and clinical interpretation rules for the classification of five facial colors in TCM diagnosis were established. (3) Key technologies for the digital recognition of facial color features were developed, and intelligent diagnosis and clinical application were realized. Digital image processing and neural network technologies were applied to establish precise segmentation algorithms for various facial regions as well as feature extraction and classification algorithms for facial color, spirit, luster, etc., achieving computerized intelligent diagnosis of facial diagnosis. The established methods were clinically validated, and the system's accuracy rate for facial color judgment was 81.25%, with luster reaching over 90%. The 'TCM Facial Diagnosis Digital Detection System' developed by this research group has been widely applied in clinical practice. The team applied this system to the facial diagnosis and syndrome analysis of chronic renal failure, chronic hepatitis B, coronary heart disease, bronchial asthma, chronic gastritis, and other five-zang diseases. The theory of facial diagnosis classification into zang-fu organs has been verified and achieved good results. (4) A large sample database of TCM facial diagnosis images has been established. Clinical experts have made macroscopic judgments and classifications on more than 20,000 collected facial diagnosis images. During the research period of this project, 5 authorized patents were obtained, including 4 invention patents and 1 utility model patent; 2 authorized computer software copyrights were obtained. 45 papers have been published, including 11 in English, 2 SCI papers (1 included, 1 source journal), and 7 EI-included papers; 23 papers have been cited 117 times, with 95 citations from others; 12 master's and doctoral students have been trained. The 'TCM Facial Diagnosis Digital Detection System' developed by this project has been promoted and applied in more than 10 medical institutions such as Shanghai and Anhui, providing visual objective data for the auxiliary diagnosis of TCM clinical syndromes and the evaluation of treatment effects. The system, as part of the digital detection instrument for the four diagnostic methods in traditional Chinese medicine, was selected as the only TCM exhibition project at the 2010 Shanghai World Expo and entered the Urban Future Pavilion for display. It was also chosen to participate in the 'Mars 500' project, a collaboration between the European Union, Russia, and China, to record the four diagnostic information (including facial diagnosis) of astronauts during a simulated 520-day interplanetary space flight to Mars, achieving significant social benefits. The further expansion of this research achievement has great significance for promoting the standardization of TCM facial diagnosis and treatment techniques and for advancing the internationalization of traditional Chinese medicine.