A portable forearm measurement scheme based on orthogonal images is proposed to achieve non-contact and accurate measurement of human forearm feature dimensions. This scheme uses a flipping mechanism to obtain orthogonal images of the front and side of the forearm, and then preprocesses the background contour of the image. The improved Otsu algorithm is used for threshold segmentation to extract the forearm contour. On this basis, morphological processing and Freeman chain code are used to remove and repair burrs and bumps on the contour edges. The characteristic size of the jib is obtained by calculating the distance from the contour edge coordinate to the minimum bounding rectangle of the jib. Finally, regression analysis was conducted using Statistical Product and Service Solutions (SPSS) software to determine the regression equation for the circumference, and the forearm circumference size was obtained by combining it with the feature size. The results show that the average error of the small arm size parameters obtained by the portable small arm measurement system based on orthogonal images is less than 5%, providing data support for the manufacturing of personalized wearable devices.