We　introduce　the　EXtract-and-COmplete　Layering　method　(EXCOL)-a　novel　cartoon　animation　processing　technique　to　convert　a　traditional　animated　cartoon　video　into　multiple　semantically　meaningful　layers.　Our　technique　is　inspired　by　vision-based　layering　techniques　but　focuses　on　shape　cues　in　both　the　extraction　and　completion　steps　to　reflect　the　unique　characteristics　of　cartoon　animation.　For　layer　extraction,　we　define　a　novel　similarity　measure　incorporating　both　shape　and　color　of　automatically　segmented　regions　within　individual　frames　and　propagate　a　small　set　of　user-specified　layer　labels　among　similar　regions　across　frames.　By　clustering　regions　with　the　same　labels,　each　frame　is　appropriately　partitioned　into　different　layers,　with　each　layer　containing　semantically　meaningful　content.　Then,　a　warping-based　approach　is　used　to　fill　missing　parts　caused　by　occlusion　within　the　extracted　layers　to　achieve　a　complete　representation.　EXCOL　provides　a　flexible　way　to　effectively　reuse　traditional　cartoon　animations　with　only　a　small　amount　of　user　interaction.　It　is　demonstrated　that　our　EXCOL　method　is　effective　and　robust,　and　the　layered　representation　benefits　a　variety　of　applications　in　cartoon　animation　processing.