Biological　pattern　formation　ensures　that　tissues　and　organs　develop　in　the　correct　place　and　orientation　within　the　body.　A　great　deal　has　been　learned　about　cell　and　tissue　staining　techniques,　and　today＇s　microscopes　can　capture　digital　images.　A　light　microscope　is　an　essential　tool　in　biology　and　medicine.　Analyzing　the　generated　images　will　involve　the　creation　of　unique　analytical　techniques.　Digital　images　of　the　material　before　and　after　deformation　can　be　compared　to　assess　how　much　strain　and　displacement　the　material　responds.　Furthermore,　this　article　proposes　Development　Biology　Patterns　using　Digital　Image　Technology　(DBP-DIT)　to　cell　image　data　in　2D,　3D,　and　time　sequences.　Engineered　materials　with　high　stiffness　may　now　be　characterized　via　digital　image　correlation.　The　proposed　method　of　analyzing　the　mechanical　characteristics　of　skin　under　various　situations,　such　as　one　direction　of　stress　and　temperatures　in　the　hundreds　of　degrees　Celsius,　is　achievable　using　digital　image　correlation.　A　DBP-DIT　approach　to　biological　tissue　modeling　is　based　on　digital　image　correlation　(DIC)　measurements　to　forecast　the　displacement　field　under　unknown　loading　scenarios　without　presupposing　a　particular　constitutive　model　form　or　owning　knowledge　of　the　material　microstructure.　A　data-driven　approach　to　modeling　biological　materials　can　be　more　successful　than　classical　constitutive　modeling　if　adequate　data　coverage　and　advice　from　partial　physics　constraints　are　available.　The　proposed　procedures　include　a　wide　range　of　biological　objectives,　experimental　designs,　and　laboratory　preferences.　The　experimental　results　show　that　the　proposed　DBP-DIT　achieves　a　high　accuracy　ratio　of　99,3%,　a　sensitivity　ratio　of　98.7%,　a　specificity　ratio　of　98.6%,　a　probability　index　of　97.8%,　a　balanced　classification　ratio　of　97.5%,　and　a　low　error　rate　of　38.6%.