Detecting　shot　boundary　plays　an　essential　role　in　video　analysis.　Conventional　methods　work　well　when　the　shot　is　cut　or　faded　in/out,　while　are　inefficient　for　dissolving　shots.　This　paper　proposes　a　novel　detection　algorithm　that　leverages　the　image　discontinuity　features　to　characterize　the　dissolving　behaviors　of　shots.　The　algorithm　consists　of　three　stages.　First,　the　image　discontinuity　features　are　employed　to　measure　the　proximities　between　of　neighboring　image　blocks　in　each　image　frame.　Then,　the　features　are　classified　by　means　of　the　SVM　classifier.　Finally,　misclassified　results　are　corrected,　and　dissolving　shots　are　extended.　The　experiments　on　TRECVid　dataset　verified　that　the　proposed　algorithm　can　achieve　much　higher　accuracy　and　robustness　compared　with　traditional　methods.