DESCRIPTOR GUIDED FAST MARCHING METHOD FOR ANALYZING IMAGES AND SYSTEMS USING THE SAME
Methods and systems for descriptor guided fast marching method based image analysis and associated systems are disclosed. A representative image processing method includes processing an image of a microelectronic device using a fast marching algorithm to obtain arrival time information for the image. The arrival time information is analyzed using a targeted feature descriptor to identify targeted features. The detection of defects is facilitated by segmenting the image. The segmented image can be analyzed to identify targeted features which are then labeled for inspection.
1 . A method for analyzing an image of a microelectronic device, comprising:
processing an image of a microelectronic device using a fast marching method to obtain arrival time information representative of features in the image of the microelectronic device; and
analyzing the arrival time information using a targeted feature descriptor to identify targeted features, if any, in the image of the microelectronic device.
2 . The method of claim 1 wherein processing the image of the microelectronic device comprises:
identifying at least one starting area of an arrival time image of the arrival time information; and
working away from the starting area to sequentially analyze the image of the microelectronic device using the fast marching method.
3 . The method of claim 1 wherein processing the image of the microelectronic device using the fast marching method includes solving an Eikonal equation.
4 . The method of claim 3 wherein solving the Eikonal equation includes converting intensities of different areas of the image to the arrival time information.
5 . The method of claim 1 wherein processing the image of the microelectronic device includes calculating the arrival time information as follows:
R|∇T|= 1
where R is a speed function based on intensity of the image and T is the arrival time information.
6 . The method of claim 5 wherein R is the intensity of the image at a pixel or cell in the image.
7 . The method of claim 5 wherein R is calculated as follows:
R
=
1
1
+
α
∇
I
where ∇I is a gradient of image intensity and α is an integer.
8 . The method of claim 1 wherein analyzing the arrival time information using the targeted feature descriptor includes:
processing the arrival time information using a segmentation algorithm; and
identifying areas of the image of the microelectronic device based on the processing of the arrival time information using the segmentation algorithm.
9 . The method of claim 8 , further comprising producing an arrival time image representative of at least a portion of the image of the microelectronic device, and wherein processing the arrival time information using the segmentation algorithm includes identifying features in the arrival time image.
10 . The method of claim 8 , further comprising identifying the targeted features in the image of the microelectronic device for visual inspection.
11 . The method of claim 10 wherein the identified targeted features are potential defects.
12 . The method of claim 1 wherein the image is a scanning electron microscope image.
13 . The method of claim 1 , further comprising analyzing the identified targeted features by processing the arrival time information using a fast marching algorithm.
14 . The method of claim 1 wherein processing the image of the microelectronic device using the fast marching method includes:
processing the image to produce a first arrival time image;
identifying at least one area of the first arrival time image; and
producing a second arrival time image based on the identified area.
15 . The method of claim 14 wherein the arrival time information includes the second arrival time image, and wherein analyzing the arrival time information using the targeted feature descriptor includes identifying features in the image of the microelectronic device based on an analysis of the second arrival time image.
16 . A method for analyzing an image of a microelectronic device, comprising:
selecting at least one starting area for an arrival time;
processing the image of the microelectronic device using a fast marching method for sequentially working away from the starting area;
producing the arrival time image based on processing of the image of the microelectronic device;
evaluating the arrival time image using a targeted feature descriptor; and
identifying targeted features, if any, in the image of the microelectronic device or the arrival time image, or both.
17 . The method of claim 16 wherein processing the image using the fast marching method includes converting intensity data of the image of the microelectronic device to arrival time information for producing the arrival time image.
18 . The method of claim 16 wherein processing the image using the fast marching method includes solving the Eikonal equation for non-starting areas of the arrival time image.
19 . A method for identifying defects of a microelectronic device, comprising:
identifying at least one starting area of an image of the microelectronic device based on an intensity of the image of the microelectronic device;
working away from the starting area to process the image of the microelectronic device to produce a processed image representative of the image of the microelectronic device;
evaluating the processed image using a defect descriptor;
identifying one or more features in the processed image using the defect descriptor; and
identifying potential defects of the microelectronic device based on the identified one or more features.
20 . The method of claim 19 wherein identifying the features includes identifying boundaries of features based on intensity.
21 . The method of claim 19 wherein identifying the features includes producing a segmented image based on the processed image.
22 . The method of claim 19 wherein working away from the starting area includes converting intensity data of the image of the microelectronic device to arrival time information using a fast marching method.
23 . The method of claim 19 wherein evaluating the processed image using the defect descriptor includes segmenting the image based on at least one threshold value of intensity.
24 . The method of claim 19 wherein evaluating the processed image includes fitting boundaries utilizing at least one of an elliptical function, a line, a curve, and/or a polygon.
25 . A system for analyzing images, comprising:
memory containing instructions; and
a programmable processing unit configured to execute instructions from the memory to:
process an image of a microelectronic device using a fast marching method to obtain arrival time information representative of a feature of the microelectronic device; and
analyze the arrival time information using a targeted feature descriptor to identify targeted features, if any, in the image of the microelectronic device.
26 . The system of claim 25 wherein the programmable processing unit is configured to execute the instructions to:
identify at least one starting area of the image; and
work away from the starting area to sequentially analyze other areas of the image using the fast marching method.
27 . The system of claim 26 wherein working away from the starting area to sequentially analyze other areas of the image comprises converting intensity data of the image to the arrival time information.
28 . The system of claim 25 , further comprising a scanning electron microscope communicatively coupled to the programmable processing unit.
29 . The system of claim 25 , wherein the programmable processing unit is configured to execute the instructions to:
produce an arrival time image representative of at least a portion of the microelectronic device based on processing of the image of a microelectronic device; and
evaluate the arrival time image based on the defect descriptor; and
identify targeted features, if any, in the image of the microelectronic device or the arrival time image, or both.