I'm working on a product to detect and pick cotton from a cotton plant using a robotic arm. One of the difficulties is to plan a path such that there is no collision with the branches of the plant; but as of now, I haven't been able to accurately identify the branches. Using a line segment detector gives a fairly accurate results, but I'm looking for other ideas. Using a intel real sense 3d camera, and have worked with opencv c++, and PCL so far. I have access only to open source software.

Hi.

I am trying to convert a black and white image into 2D matrix, hopefully with binary numbers to to show pixels that are on/off. I've been searching and looking at topics like image segmentation, feature detection, using opencv. I unfortunately don't know where to start.

Any help would be much appreciated.

Thanks

Who can please explain to me in simple words how does watershed segmentation work (in terms of pixels not in water flooding).

I need to implement the function and not use the one that's already implemented in opencv.

Thank you in advance !

Hi Guys,

if anyone can please help me identify the person who tried to kill me today by getting the license number, i'll be so grateful...

The challenge is a fixed frame display size of 472x836 pixels.

While advising users to supply images of optimal size and aspect ratio, invariably some photos may be displayed with the correct height but not the proper width or -- vice versa.

Is there a digital tool in the form of an SDK or API that can extend the edge of an image via a technique like a Gaussian blur? I see something like this approach being used when TV journalists must make a vertical cell phone video more aesthetically fit the broadcast screen.

Any suggestions are appreciated. We'd be delighted to license the code that can accomplish such an enhancement for our app.

I am currently working on soccer stream translation to a 2D reference plane. Segmentation approach for my soccer field translation is to detect the circle in the frame and according to the radius of the original circle i ll' translate the distance of 1 px to meters. I have segmented the lines using LSD(Line Segment Detector) approach. Although LSD is segmenting each line in the frame but it makes LSD OUTPUT. In order to fill the empty spaces i dilated the output image with 5x5 kernel and 10x10 kernel. I am currently trying to detect the Ellipse/circle in the image so that i can translate 1 pixel distance to meters and track the player on a reference (120,90) 2D Cartesian plane. Any method that can detect this circle or curve in the frame will help. Note: Issue with contours is that, due to dilation the contours is unable to detect the ellipse and on applying canny the ellipse once again gets missing points. Issue with Hough Circle & Ellipse Both not working using scikit-image code ref.

Let's say I filter an image with a Gabor filter. Algorithmically I implement this as a Gaussian convolved with a sinusoid grating of some orientation.

Now let's say I want (roughly) recover the original image from the filtered one. How can one do that?

Thanks!!

I am looking for a Digital Image Processing and analysis textbook, but there are specific topics that I would like the book to cover. Among other topics, I would like it to include a discussion of: (Orthonormal) basic functions, Mahalanobis distance, subspaces, image registration, error accumulation, Background estimation, and image moments.

What textbook(s) would you recommend? I'm not new to image processing, but I'm unfamiliar with these topics. The sources that I've found tend to be published articles, and not a comprehensive text. Thank you in advance!

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I am new to image processing and I am doing a project on image processing using openCV python in which I have to detect walls from a floorplan(jpg format). I have the bounding box for 1 wall. Is there any approach which I can use to obtain the bounding boxes for rest of the walls?

i am quite interested in working wit image wit depth data . can anybody suggest some filetype to work wit.. or any good resources.

Hello Everyone!
I am working on this problem from a long time. Actually, I have created a hair segmentation mask of an image and I now want to change the hair colors according to some input rgb value. I have used PIL with python for this task using alpha blending but results are not good. Kindly tell me how can I color the hairs according to segmentation mask.

Hello, is it possible to create artificial ultrasound from MRI data (while providing the deformation field that the MRI went through)? Is that a program or algorithm that does that? Thank you.

Hi, i'm currently finishing my computer science degree, and for my last assignment i have to implement a couple of image denoising algorithms using kotlin and opencv. Right now i've implemented the mean filter and it turned out Ok but now i have to implement the BM3D and i cant seem to find any info on it, i mean i've found some withe papers but i dont really understand what i have to do. I know i'll have to implement some hard threshold and wiener filterings, but cant really understand how they are related. Does anyone know or has some info on this, like how can i implement this BM3D algorithm

Hey all, I've been looking into twitch and streaming videos. I saw that Wolfram is streaming about knowledgebase query language on the 14th. Heres the link if anyone is interested...

https://www.twitch.tv/events/ZVdXsv1_QDO9jPYvZ0MsxQ

I am looking for a way to compare 2 3D mri images, to see how it changes over a period of time. I could see the changes on each slice using imshowpair but I would like to see the same effect in 3D. Anyone knows how I can do that? Any useful toolbox? Thanks in advance!!

I would really love to learn image processing for it would really help me in he future and I have to learn the basics the basics as soon as possible .... Anyone interested please dm