We recently proposed a new approach for the segmentation of speckled images based on active contours (snakes) [e.g., Opt. Commun. 137, 382 (1997)]. We propose an extension of this approach to multichannel data. Two solutions are compared based on hypotheses on the possible mean intensity variation between the channels. Each solution is optimal for a certain class of input images, but one solution shows better or equivalent performance for both input image classes. This result opens new perspectives for the segmentation of multichannel images with the snake-based approach.