003 for (j=0;j<NUM_NEIGHBORS;j++)/* for all neighbors of next node */
The loop variable j selects the row in the energy/direction table. The range of this variable corresponds to a 3x3 grid centered around the current position of the snaxel. This computes the minimum energy over all possiblepositions to move this snaxel; that energy is later stored in the energy matrix.
006 for (k=0;k<NUM_NEIGHBORS;k++) /*for all neighors of curr node*/
007 {
008 nextNode = snaxel[i+1] + neighbor[j]
009 currNode = snaxel[i] + neighbor[k]
010 energy = energyMtx[i-1][k] + E(currNode, nextNode)
011 if (energy < min_energy)
012 {
013 min_energy = energy
014 min_position = k
015 }
016 }
In this loop, we are finding the minimum over k in the following equation.
We are building an energy table for the snaxel, translated to its
neighbor. Each
entry in the table represents the minimum energy associated with each
possibility for the choice of the
snaxel. We search over all possibilities in our
chosen neighborhood (indexed by k) for the
snaxel and compute the
corresponding energy. We then pick the minimum over these
possibilities and store that energy in the table along with which
neighbor was chosen for
.
When we have done this for each
neighbor, we have built one column
in the energy table.
This part of the code comes from the paper by Amini, pp. 861 - 862 , equations 52 & 53.
017 /* Store minimum energy into table */ 018 energyMtx[i][j] = min_energy 019 posMtx[i][j] = min_position
These two lines store in the table the minimum energy and position yielding this energy corresponding to the ith snaxel and its jth neighbor.
023 /* search final column for minimum energy */
This loop searches the last column of the table to find the minimum energy and to determine a starting point for the backwards iteration that will give the updated optimal snaxel positions.
035 /* search backwards through table to find optimum postions */
This loop takes as its starting point, the position of the minimum of the last column of the energy matrix, and updates the last snaxel to reflect the best choice for that snaxel. It then uses the corresponding value in the position matrix as the next starting point. This is repeated until the whole snake is updated (number of iterations is NUM_SNAXELS-1). This completes one execution of the algorithm.