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Upper gastrointestinal endoscopies are primarily performed to observe the pathologies of the esophagus, stomach, and duodenum. However, when an endoscope is pushed into the esophagus or stomach by the physician, the organs behave similar to a balloon being gradually inflated. Consequently, their shapes and depth-of-field of images change continually, preventing thorough examination of the inflammation or anabrosis position, which delays the curing period. In this study, a 2.9-mm image-capturing module and a convoluted mechanism was incorporated into the tube like a standard 10- mm upper gastrointestinal endoscope. The scale-invariant feature transform (SIFT) algorithm was adopted to implement disease feature extraction on a koala doll. Following feature extraction, the smoothly varying affine stitching (SVAS) method was employed to resolve stitching distortion problems. Subsequently, the real-time splice software developed in this study was embedded in an upper gastrointestinal endoscope to obtain a panoramic view of stomach inflammation in the captured images. The results showed that the 2.9-mm image-capturing module can provide approximately 50 verified images in one spin cycle, a viewing angle of 120° can be attained, and less than 10% distortion can be achieved in each image. Therefore, these methods can solve the problems encountered when using a standard 10-mm upper gastrointestinal endoscope with a single camera, such as image distortion, and partial inflammation displays. The results also showed that the SIFT algorithm provides the highest correct matching rate, and the SVAS method can be employed to resolve the parallax problems caused by stitching together images of different flat surfaces.
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