Tag Archives | image processing

Long exposure with OpenCV and Python

One of my favorite photography techniques is long exposure, the process of creating a photo that shows the effect of passing time, something that traditional photography does not capture. When applying this technique, water becomes silky smooth, stars in a night sky leave light trails as the earth rotates, and car headlights/taillights illuminate highways in […]

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Seam carving with OpenCV, Python, and scikit-image

Easily one of my all-time favorite papers in computer vision literature is Seam Carving for Content-Aware Image Resizing by Avidan and Shamir from Mitsubishi Electric Research Labs (MERL). Originally published in the SIGGRAPH 2007 proceedings, I read this paper for the first time during my computational photography class as an undergraduate student. This paper, along with […]

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Detecting machine-readable zones in passport images

Today’s blog post wouldn’t be possible without PyImageSearch Gurus member, Hans Boone. Hans is working on a computer vision project to automatically detect Machine-readable Zones (MRZs) in passport images — much like the region detected in the image above. The MRZ region in passports or travel cards fall into two classes: Type 1 and Type 3. Type 1 […]

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Watershed OpenCV

The watershed algorithm is a classic algorithm used for segmentation and is especially useful when extracting touching or overlapping objects in images, such as the coins in the figure above. Using traditional image processing methods such as thresholding and contour detection, we would be unable to extract each individual coin from the image — but by leveraging the […]

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OpenCV Gamma Correction

Did you know that the human eye perceives color and luminance differently than the sensor on your smartphone or digital camera? You see, when twice the number of photons hit the sensor of a digital camera, it receives twice the signal (a linear relationship). However, that’s not how our human eyes work. Instead, we perceive double the amount […]

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