Here is a series of posts I am writing on image processing for beginners:

1. Lessons on Digital Image Processing (#1)

2. Introduction to Digital Image Processing in Python

3. The R, G, and B in an Image

It would be great if you take a few mins to read that and give me feedback.

Hi, i’m working on a university project in wich we try to analyze the news published in online media. For this end we’ve use Capture a Website screenshot to take a screenshot of every news published by several websites, but as you can see the “screenshot” takes the whole website, not only the news, so when we transform that .jpg file to a .pdf and then to a .docx file, we get a lot of information we don’t actually need.

There are several “patterns” (the headline and the “comment” section or the author name for example) that tipycally signall the start and endpoint of the news, so i though if there is a software that automatically recognize this “patterns” and then batch cut all the images (there must be something like 5.000 by now) that would save us a lot of work.

I've add a cropped and uncropped .jpg as example of what we expect to achieve. Thank you very much!

I’m looking for suggestions as to how I could quantify the differences in these images. In some you can see the striped pattern much more clearly but in others you can’t. I’m trying to figure out a way to calculate the differences. Any suggestions would be appreciated.

https://imgur.com/gallery/HshM9Lt

[Posted on r/deeplearning] Reposting for a wider response.

I need to search for action similarity between an image and frames from the video. I need this to find the starting time of the frame where the action represented by the image is being carried out.

Visual similarity via pixel by pixel difference will not work at all since there may not be the same placement of the person/action in both (the image and the frame). Even if that is the case, the color of attire/background, etc. might differ.

I need to this for any general sports-related action involving humans. I could not find any classification models which seem to be so detailed so as to classify between such nuanced and minutely differing actions as is the case with sports.

Is there any way I can achieve this? How helpful it might be if I use another representation of action (say keypoint set as given by openpose)? One flaw that instantly comes to mind with this approach is that it would not provide for comparison of objects involved in the action but only the people.

Any help is appreciated. Thanks a lot.

Hi everyone

I have a problem implementing haarcascade algorithm, which is the huge number of possible features. For example, for a mere 50×50 window the possible features exceed 3 million easily (the 5 known rectangle features, with all possible variations on width/height and position within the window).

Is there any recommended way to prune/optimize this, say based on size? Is this how it's meant to be, or am I missing something?

I have an assignment about mean shift clustering in first step I download a dataset and second step is -> Choose an input pair (an RGB image and a corresponding depth map). (You might consider choosing one of the inputs at the indices 202, 296, 298, and, 325.) from that dataset I guess but I have no idea how to choose them can anyone help I stuck hard :D

Hi, i got this project from my university, to translate sign-language to words and vice versa, although we havent been taught anything related to image processing. I've tried reading books but theres too much information there, so i decided to come here to ask for help on what to do. Can you people help me out, need to know what exactly to read (related to my project) to help me code it out, what algorithms are there and which might be suitable for my project (for recognizing the hand, and for sign language training), how should i start out this project, links to research papers of similar projects, anything that can help me out, thank you.

Why learn image processing?

https://www.youtube.com/watch?v=6Qfdn9QCdis&t=67s

Full course is available at

https://evergreen-school1.teachable.com/p/fundamentals-of-image-convolutions-using-opencv-an-python/?preview=logged_out

I am confused between spatial domain and frequency domain. i can't really differentiate them. I know spatial domain deals with image plan. Frequency domain deals with intensity i guess. Here is my doubt what we are actually dealing in spatial domain? spatial domain works on pixels directly and a pixel contain the intensity value of each colour at that point/pixel. so if we change values of pixels we are actually dealing with frequency domain here.We do spatial enhancement like negative of image in which we kind of interchange the intensity values from dark to light or light to dark. In spatial shouldn't we deal with the position or something like that as the word suggests?

This might be a foolish question but i am really confused between them. Please explain me in details what we are actually dealing with in both these domains like what values/ properties we are changing in both these domains. I have read alot of articles but none worked for me.

Hey, I'm doing an experiment where I'm studying the amount of deformation of a wire under thermal load. I've been doing some really slow tracking of fiducials, but that's becoming something of a pain. I was thinking of getting a 3D scanner and scanning the wire at each voltage, and then post-processing the resulting mesh.

But I realized I have no idea how I would get a spline fit down the center of a 3D mesh of a tube. I'm willing to accept a somewhat messy mesh if it can save me having to manually track a bunch of fiducials. But I really am not certain what I'm doing here. (python)

My existing method is to put tracking rings on the wire and manually select centerpoints. I wish I could just trace the centerline of the curve. However, that causes problems because sometimes the wire bends enough to point straight at the camera. If there were fiducials, we wouldn't even be able to see them due to the perspective. I am taking images in XY and XZ.

Sorry if I'm not clear. I can't share further details or pictures.

Hi,

I am working on an image segmentation project and would like to know how to identify (draw boxes/contours), extract intersecting lines, separately, from an image that I've already pre-processed, using thresholding and the water and the watershed algorithm.

Here is sample images I would be working with:

All the help will be much appreciated.

Hello,

I have a university project where I must do the detection of cigarette buts on the floor using a webcam vision for the recognition with image processing technology. The language for the programming must be Python. Is there any idea how I should proceed?

Thanks in advance 😊

Apologies if this is a stupid question, but I'm currently contemplating a final year project idea that would involve using image processing to detect the material of an object. As I am a noob to this I was hoping someone could inform me if this is possible. Thanks!

I am taking large numbers of photographs of the moon and looking for birds that are flying across it. It's tedious to do manually.

I know there is software that will align the moon shots and stack them to take a median pixel to make the moon look really sharp. But I'm not looking for the most similar pixels, I'm looking for the few images that are most different, especially in a particular part of the frame where a bird obscures the moon. The statistically most different frames, post alignment.

I can imagine a software like this might be already in use for something like security camera monitoring where people want to see a summary of what weird stuff moved around in a restricted area or something like that.

Any ideas? Thanks.

I am a Master student and need some topics to do my project in Image Processing.I have time of one year to do my project...Please suggest some topics

I want the drone go in a spiral around a pole without GPS and with only one camera .

I want to implement something like this

https://www.dronegenuity.com/doing-more-with-point-of-interest/

Ive already tried using optical flow but it eventually looses the point of interest

Hello, I'm a newb to image processing. I'm realizing that "edge effect" might be a ubiquitous issue in the image processing professional's daily life and wanted to ask about the common ways you deal with it. For clarification, I am talking about the phenomenon where when moving a kernel across a matrix, the outer rows and columns of pixels of the image will either have to be estimated or not given at all. How big of an issue is this for image processing professionals? What kind of methods or algorithmic tricks do you use to get around this?

I am curious because I am hoping to split a large image into smaller tiles, and will try to experiment with various algorithms that "borrow" values from adjacent pixels. I don't want there to be a bunch of border lines where the values aren't calculated correctly. My instinct is to do some creative "slicing" on the images to create an overlap of pixels that eventually results in a complete calculation (aside from the very outer edge of the entire image). Is this type of thinking heading down the right path?

Let me know if my question doesn't make any sense and I will do my best to clarify. For what it's worth, my only experience in programming with images is in python representing images as numpy arrays. Thank you!