This paper investigates a number of verification rules to validate the segmentation of connected handwritten digits. The verification technique based on statistical reasoning and fuzzy integrals is employed to verify the segmentation through decision functions produced by multiclass SVM based recognizers. The segmentation relies on an oriented sliding window which identifies potential cut points. The resulting segmented digits are fed to recognizers and the best segmentation is identified by the verification module that combines the recognizer outputs using fuzzy integrals. The proposed methodology is evaluated on a database of handwritten digits with single as well as multiple connections. Comparative analysis shows that the use of the fuzzy integral allows providing high recognition rates comparatively to the state of the art.