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Open-source Java libraries, supporting generalized smart arrays and matrices with elements
of any types, including a wide set of 2D-, 3D- and multidimensional image processing
and other algorithms, working with arrays and matrices.
/*
* The MIT License (MIT)
*
* Copyright (c) 2007-2024 Daniel Alievsky, AlgART Laboratory (http://algart.net)
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
package net.algart.matrices.skeletons;
import net.algart.arrays.*;
import java.util.Objects;
abstract class AbstractThinningSkeleton2D
extends AbstractIterativeArrayProcessor>
implements ThinningSkeleton
{
final boolean straightThinning;
final boolean diagonalThinning;
final MemoryModel mm;
Matrix result;
Matrix temp;
private long cardinality = -1;
boolean done = false;
AbstractThinningSkeleton2D(ArrayContext context, Matrix matrix,
boolean straightThinning, boolean diagonalThinning)
{
super(context);
Objects.requireNonNull(matrix, "Null matrix argument");
this.mm = ErodingSkeleton.mm(memoryModel, matrix, 1);
this.result = matrix;
this.temp = mm.newMatrix(UpdatableBitArray.class, boolean.class, matrix.dimensions());
this.straightThinning = straightThinning;
this.diagonalThinning = diagonalThinning;
}
@Override
public final void performIteration(ArrayContext context) {
ArrayContext c = cardinality == -1 ? part(context, 0.02, 0.98) : part(context, 0.02, 1.0);
if (cardinality == -1) {
cardinality = Arrays.cardinality(part(context, 0.0, 0.02), result.array());
}
long lastCardinality = cardinality;
double part = straightThinning && diagonalThinning ? 0.125 : 0.25;
for (int k = 0; k < 8; k++) {
if (!isThinningRequired(k)) {
continue;
}
Matrices.copy(part(c, k * 0.125, Math.min(k * 0.125 + part, 1.0)), temp, asThinning(k));
Matrix t = temp; temp = result; result = t;
}
cardinality = Arrays.cardinality(part(context, 0.98, 1.0), result.array());
done = cardinality == lastCardinality;
}
@Override
public final boolean done() {
return done;
}
@Override
public abstract long estimatedNumberOfIterations();
@Override
public final Matrix result() {
return result;
}
@Override
public final void freeResources(ArrayContext context) {
temp.freeResources(context == null ? null : context.part(0.0, 0.5));
result.freeResources(context == null ? null : context.part(0.5, 1.0));
}
public final boolean isThinningRequired(int directionIndex) {
if (directionIndex < 0 || directionIndex > 7) {
throw new IllegalArgumentException("Illegal directionIndex = " + directionIndex + " (must be 0..7)");
}
return directionIndex % 2 == 0 ? straightThinning : diagonalThinning;
}
public abstract Matrix asThinning(int directionIndex);
}