This could be a start. This is not as solid/stable as what ImageAnalyst proposes though. In French we would call that "bricolage" ;-)
I = im2bw( imread( 'hand.jpg' )) ;
% - Crop white frame.
I = I(~all(I,2),~all(I,1)) ;
% - Crop 10px border to eliminate glitches at the border.
I = I(10:end-10,10:end-10) ;
[nRow, nCol] = size( I ) ;
% - Find first horizontal transition 0->1 from left.
D = diff( I, 1, 2 ) == 1 ;
% - Find first column per row where D is 1.
[~, colId] = max( D, [], 2 ) ;
% - Smoothen colId.
kerSize = round( nCol /10 ) ;
colId_smz = conv( colId, ones( 1, kerSize )/kerSize, 'same' ) ;
figure() ;
set( gcf, 'Units', 'normalized', 'Position', [0.1,0.1,0.8,0.8] ) ;
% - Plot cropped image.
subplot( 2, 2, 1 ) ;
imshow( I ) ;
title( 'Cropped image' ) ;
% - Plot left profile.
subplot( 2, 2, 2 ) ;
imshow( D ) ;
title( 'Left profile' ) ;
% - Plot left profile + smoothen.
subplot( 2, 2, 3 ) ;
y_colId = colId ; y_colId(colId==1) = NaN ;
y_smz = colId_smz ; y_smz(colId==1) = NaN ;
plot( 1:nRow, y_colId, 'b', 1:nRow, y_smz, 'r' ) ;
grid on ; title( 'Profile + smoothen' ) ;
% - Plot difference + smoothen.
subplot( 2, 2, 4 ) ;
dif = diff( y_smz ) ;
dif_smz = conv( dif, ones( 1, kerSize )/kerSize, 'same' ) ;
plot( 1:nRow-1, dif, 'b', 1:nRow-1, dif_smz, 'r' ) ;
ylim( prctile( dif_smz, [5, 95] )) ;
grid on ; title( 'Diff + smoothen' ) ;
With that you get:
Then you have to detect the from the right the point where the smoothen derivative changes significantly.
