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Questions tagged [cbir]

Content-based image retrieval is a method for retrieving images from databases by using the actual content of images. Given an input query image, images returned from the database are those that look visually similar to the query, or those that have similar features to the query.

Content-based image retrieval (CBIR), also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR) is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases. (see this survey1 for a recent scientific overview of the CBIR field). Content based image retrieval is opposed to concept based approaches. wikipedia

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Histogram comparation for Content Based Image Retrieval. Different color spaces (RGB,HSV,etc..)

I'm doing a final degree proyect in Content Based Image Retrieval using OpenCv. I have started comparing histograms. The thing is that I have seen a lot of post saying that RGB is the worst color space to operate, and it's better to use HSV or YCrCb…
mapetilan
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What can i use better than ORB for matching photos

I have folder named with a lot of location and each of them have 360 degree pics of each of those location i give it a random picture and it has to guess where am i, I tried ORB and it gave me good results and i made it better also but the issue is…
REUBEN RENY
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find template image in directory of images

I have a directory of images and an image that I know is in this image directory there is a similar image in the directory saved in a different format and scaled differently, but I dont know where (about 100 000 images). I want to look for the image…
Arimodu
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How to evalaute a CBIR model performance without ground truth?

I implemented a content-based image retrieval(CBIR) model using Convolutional Autoencoders (neural networks). When given a query image to the model, I get five retrieval results from the database. But to evaluate the CBIR model, there is no ground…
raghu varma
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Extracting GLCM features

So I was going through a research paper [link], which has the following Algo for getting the texture of the image. So what i understand from the above algo is that I need make grids of 4x4 and find the GLCM matrices for each of those 4x4 sub…
XXDIL
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How to access apache solr server installed at google colab online?

I am using Google Colab for apache solr 8.5.0 server implementation of Content Based Image Retrieval (CBIR) system, The solr is showing its port (8983), along with this, i have tried couple of IP addresses to access the solr server but…
Jawad Ali
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Is it normal that I have so poor results in my CBIR system?

I am building a CBIR system with Corel Database (100 classes of 100 pictures). I have implemented some "current" (non deep learning) descriptors (Sift, Surf, HOG, Color Histogram, HSV histogram, LBP histogram, ORB, Hu Moments of the image, GLCM…
MysteryGuy
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Using sift descriptors with a classification algorithm

I'm trying to make a simple image search engine using Oxford Buildings Dataset First I used SIFT to extract features. Basically I iterated over every image in dataset and generate key points and descriptors for everyone of them. Then, I choose one…
user1234
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Compute Recall and Precision to evaluate CBIR system

I implemented a CBIR with SIFT combined with other feature-based algorithms (with OpenCV and Python3), now I have to evaluate how the combination of them (i.e. SIFT/SURF, ORB/BRISK...) perform. I found that I can use Precision |TP| / (|TP| + |FP|)…
Furin
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How to use FLANN for labeling and clustering?

I read a paper that their retrieval system is based on SIFT descriptor and fast approximate k-means clustering. I installed pyflann. If I am not mistaken the following commands only find the indices of the close datapoints to a specific sample (for…
S.EB
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How to store large feature vectors for a huge dataset for image retrieval application (CBIR)?

I am building a CBIR application . I am using the features extracted from a deep convnet. The feature vectors are quite big ( about 100,000 in size) . And the dataset has more than 10k images. I have already gone through the answer to this…
Arko1696
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Neural Networks Descriptors in Approximate Nearest Neighbor for Image Retrieval

Disclamer: I don't know nothing about Neural Networks or deep learning. VLAD and Fisher Vectors with Product Quantization are a good example of how Approximate Nearest Neighbor can be used for good image retrieval. However, it has been proved how…
justHelloWorld
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Binary descriptors: find the most similar image in OpenCV with LSH

flannIndex in openCV is designed for matching 2 images through binary descriptors. Anyway LSH is heavily used in CBIR in order not to "comparing two images" but "find the most similar image in the dataset", which is obviously something…
justHelloWorld
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CBIR system - restriction to retrieve top twenty matching images produces same curves of precision, recall and f-measure

I want to know if this restriction is even a valid option? Because we can't judge the precision recall, f-measure tendency independently. If it's ok then how to justify the same tendency of all precision, recall and f-measure curves? I have used a…
Zain Khan
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Retreiving similar images from a set of images using SIFT/SURF

I am working on SIFT features and 'm using a visual bag-of-words approach to make a vocabulary first and then do the matching. I've found similar questions but didn't find the appropriate answer. Same question is asked in below link but there is no…
Nilkanth Khajure
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