| Submission declined on 25 April 2024 by Utopes (talk). This draft's references do not show that the subject qualifies for a Wikipedia article. In summary, the draft needs multiple published sources that are:
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Comment: Not enough quality sources, no need to use an external link to send someone to a research paper, is written more like an essay/lecture notes than an encyclopedia article. (I wrote "lecture notes" before realizing that those, too, were also included in the external links.) Would need to be largely rewritten into prose form. Utopes (talk / cont) 22:53, 25 April 2024 (UTC)
Point Detection edit
In digital image processing, Image segmentation algorithms are generally based on two properties: discontinuity and similarity. [1] In Discontinuity property, partition of image is based on abrupt changes in pixel intensities. examples are: Point detection, Line detection, Edge detection. On the other hand, similarity-based segmentation techniques group pixels based on their similarity in color, texture, or other features. examples of these method are: Region growing, K-means clustering, Mean shift, Graph cuts in computer vision, Fuzzy clustering, Active contour model. Point detection algorithms aim to identify isolated points or locations in an image where there is a significant change in intensity compared to the surrounding pixels.
[2]
Discontinuity Detection is usually accomplished by applying a suitable mask to the image.
A general 3 * 3 mask:
[3]
| w1 | w2 | w3 |
|---|---|---|
| w4 | w5 | w6 |
| w7 | w8 | w9 |
The procedure involves computing the sum of products of the coefficients with the gray levels contained in the region encompassed by the mask. [4]
where zi is the gray level of the pixel associated with mask coefficient wi.
F (image pixels)=
| z1 | z2 | z3 |
| z4 | z5 | z6 |
| z7 | z8 | z9 |
W (this mask will be putted on every pixel of image)=
| -1 | -1 | -1 |
| -1 | 8 | -1 |
| -1 | -1 | -1 |
A =
| R | ||
For any point P at (x,y) position,
If |R| > Threshold
Then
point is said to be detected at (x,y) position. this formulation measures the weighted differences belween the center point and its neighbors. the idea is that an isolated point (a point whose gray level is
significantly different from its background) will be quite different from its surroundings, and thus be easily detectable by this type of mask.
This point detection technique is written in book: Digital Image Processing by Gonzalez, Rafael C.; Woods, Richard E. link Also you can check lecture notes of Washington State University here, research paper
- ^ Washington State University. (n.d.). Lecture 21: Edge Detection. Link
- ^ University of Nevada, Reno. (n.d.). Corner Detection. Link
- ^ Gonzalez, Rafael C.; Woods, Richard E. (2002). Digital Image Processing (2nd ed.). Upper Saddle River, New Jersey: Prentice Hall. p. 812. ISBN 978-0201180756.
- ^ Kumar, Rajiv (2014). "Image Segmentation using Discontinuity-Based Approach". ResearchGate. Retrieved 2024-04-23.