The　image-based　deformation　analysis　method　(IDA)　is　currently　an　important　deformation　testing　technology　in　the　field　of　soil　mechanics　and　geotechnical　engineering.　The　speckle　images　are　a　common　tool　for　the　development,　application　and　reliability　evaluation　of　the　IDA;　whether　they　represent　the　characteristics　of　actual　soil　particles　and　are　suited　to　assess　the　reliability　of　the　IDA　or　not　remains　to　be　answered.　By　choosing　the　Fujian　standard　sand　as　a　sample,　a　generation　method　for　synthetic　images　describing　the　image　and　deformation　characteristics　of　actual　sands　is　addressed　through　the　analysis　of　characteristics　of　sand　images　as　well　as　their　comparison　to　speckle　images.　Using　the　proposed　method,　four　types　of　sequential　deformation　images　with　analytical　formulas　of　the　coordinates　are　generated　to　evaluate　the　reliability　of　two　representative　RG-DIC　and　PIVlab　approaches.　The　results　show　that　the　speckle　images　have　remarkable　differences　compared　to　the　actual　sand　ones　in　texture,　roundness　and　color　values.　The　proposed　generation　method　for　synthetic　images　is　capable　of　modifying　the　distribution　parameters　of　particle　size,　roundness　and　color　value,　reflecting　the　characteristics　of　the　actual　soil　images.　By　introducing　time　variable　and　arbitrary　deformation　functions,　the　generated　sequential　deformation　images　enable　the　reliability　evaluation　of　IDA　on　dynamic　and　complex　deformation.　The　speckle　images　apparently　underestimate　the　analysis　error　of　both　the　RG-DIC　and　the　PIVlab　methods,　due　to　the　black　background　and　white　circular　spots　with　higher　degree　of　recognition　than　the　texture　and　particle　features　of　the　actual　sand　images.　The　deformation　analysis　in　accuracy　and　stability　from　the　RG-DIC　exhibits　more　preferable　than　that　from　the　PIVlab.　The　trends　of　analysis　error　under　various　deformation　conditions　using　the　two　methods　are　in　good　agreement,　and　while　the　shear　strain　is　smaller　than　10-3,　the　analysis　error　increases　rapidly.　The　proposed　method　and　results　provide　important　supports　and　references　for　the　development,　application　and　reliability　evaluation　of　soil　image-based　deformation　analysis　methods.　©　2024　Chinese　Society　of　Civil　Engineering.　All　rights　reserved.