Selecting high-quality seeds is an effective approach for increasing wheat yields. Phenotype-based seed selection has emerged in recent years as a simple and convenient method. However, due to the irregular shape of seeds, accurately measuring shape parameters via imaging for seed viability assessment poses certain challenges. This study statistically analyzed the embryo morphology of wheat variety Bainong 207, identifying three predominant phenotypes. The morphological parameters of seeds and embryos were measured for these three phenotypes. Germination tests were conducted on these three categories of wheat in accordance with Chinese national standards. The seeds with Phenotype Ⅰ exhibited the highest germination force (89.33%) and the highest germination percentage (96.00%), representing a statistically significant difference from Phenotype Ⅱ and Ⅲ. Morphological parameters related to seed vigor, including germinative force, germination percentage, seedling height, and root length, were measured. By exploring the relationship between embryo phenotypes and wheat seed viability and yield potential, principles and considerations for wheat seed selection based on embryo phenotypes were discussed. The YOLOv8 model was employed to classify wheat seeds with different embryo phenotypes. Under the global labeling of seeds, the classification accuracy for the three categories reached 99.9%. Classification results from various labeling methods were compared, validating the feasibility of machine vision for seed selection and providing technical support for large-scale wheat seed improvement.