To accurately determine the inner diameter contour of a microscopic image of a harness terminal for subsequent data analysis, a microscopic image segmentation algorithm based on variable exponential filtering is proposed in a chromaticity-brightness space. First, based on the color distribution characteristics of the microscopic image of a color wire harness terminal, color images in the red, green, and blue color space are converted to the chroma brightness space. In addition, lighting effects and separate luminance and chrominance information are eliminated, and chrominance information is converted to chroma spheres. Next, based on the total variation model, a variable exponential variational model on a chromaticity sphere is constructed to filter the chrominance information, where the variable exponential function is shown to have structural adaptive properties. Then, following analysis of the edge detection result of the monochrome channel, the Canny algorithm is used to perform edge detection in the red channel of the image. After the false discontinuous boundary curve is removed, the final inner diameter contour is obtained. Experimental results show that the circumference of the inner diameter of the terminal obtained by this method is compared with the manual measurement, and the deviation is less than 0.5%. The data regarding the inner diameter contour and circumference of the terminal obtained by the algorithm are also shown to be accurate.