Class Canny

java.lang.Object
  |
  +--java.lang.Thread
        |
        +--Canny

public class Canny

extends java.lang.Thread

Canny is an algorithm to apply the canny edge detector to an image

See Also:

code.iface.canny

Fields inherited from class java.lang.Thread

MAX_PRIORITY, MIN_PRIORITY, NORM_PRIORITY

Constructor Summary

Canny()

Method Summary

int[]

apply_canny(int[] src_1d, int width, int height, int size, float theta, int lowthresh, int highthresh, float scale, int offset) Applies the canny edge detector to the input image

Methods inherited from class java.lang.Thread

activeCount, checkAccess, countStackFrames, currentThread, destroy, dumpStack, enumerate, getContextClassLoader, getName, getPriority, getThreadGroup, interrupt, interrupted, isAlive, isDaemon, isInterrupted, join, join, join, resume, run, setContextClassLoader, setDaemon, setName, setPriority, sleep, sleep, start, stop, stop, suspend, toString, yield

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

Canny

public Canny()

Method Detail

apply_canny

public int[] apply_canny(int[] src_1d,
                         int width,
                         int height,
                         int size,
                         float theta,
                         int lowthresh,
                         int highthresh,
                         float scale,
                         int offset)

Applies the canny edge detector to the input image

Parameters:

src_1d - The source image as a pixel array

width - width of the destination image in pixels

height - height of the destination image in pixels

size - The size of the kernel used in the smoothing

theta - The gaussian smoothing standard deviation

lowthresh - The low threshold for the tracking

highthresh - The high threshold for the tracking

scale - The amount of scaling to be applied to the image

offset - The amount to be added to each result pixel

Returns:

A pixel array containing edges in the image