roberts

roberts ( Image : ImageRoberts : FilterType : )

Detect edges using the Roberts filter.

roberts calculates the first derivative of an image and is used as an edge operator. If the following mask describes a part of the image,

                        A               B

                        C               D

the different filter types are defined as follows:

   'roberts_max'     max(| A - D |,| B - C |)
   'gradient_max'    max(| A + B - (C + D)|,| A + C - (B + D)|)
   'gradient_sum'    |A + B - (C + D)| + |A + C - (B + D)|

If an overflow occurs the result is clipped. The result of the operator is stored at the pixel with the coordinates of "D".

Parameters

`Image` (input_object)	(multichannel-)image(-array) `->` object : byte / int2 / uint2
Input image.

`ImageRoberts` (output_object)	(multichannel-)image(-array) `->` object : byte / int2 / uint2
Roberts-filtered result images.

`FilterType` (input_control)	string `->` string
Filter type.
Default value: 'gradient_sum'
List of values: 'roberts_max', 'gradient_max', 'gradient_sum'

Example

read_image(Image,'fabrik') 
roberts(Image,Roberts,'roberts_max') 
threshold(Roberts,Margin,128,255).

Result

roberts returns 2 (H_MSG_TRUE) if all parameters are correct. If the input is empty the behaviour can be set via set_system('no_object_result',<Result>). If necessary, an exception handling is raised.

Parallelization Information

roberts is reentrant and automatically parallelized (on tuple level, channel level, domain level).

Possible Predecessors

gauss_image

Possible Successors

threshold, skeleton

Alternatives

edges_image, sobel_amp, frei_amp, kirsch_amp, prewitt_amp

Module

Foundation