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It turns grayscale into binary: - bright pixels → white- dark pixels → black- Useful for segmentation (separating objects from background). T \\0 & \text{otherwise}\end{cases}\)">\( \mathrm{dst}(x,y)= \begin{cases} 255 & \text{if } \mathrm{src}(x,y) > T \\ 0 & \text{otherwise} \end{cases} \) For example, Contours Contours are curves joining all continuous points along the boundary having the s..

A filtering technique that uses a Gaussian function to create a smoothing effect on an image. The blur reduces image noise and reduces detail by averaging pixel values with their neighbors.- it suppresses high frequency noise, keeps larger scale structure, makes gradients reflect real boundaries.- When we apply Gaussian Blur, we create a kernel (a small matrix). The kernel is then convolved with..

There is a sharp change in intensity a sharp change in color. Image can be read as a matrix an array of pixels that contains the light intensity at some location. 0 : no intensity if something is completely black255 : maximum intensity that something being completely white a strong gradient : a steep changea small gradient : a shallow change Canny Edge Detection A popular edge detection algorit..

Object Detection - Image Classification = (single object) Classification- Image Localization = (single object) Localization, predicting the location of a single object in the Bounding Box.- Object Detection = (multi objects) Localization + (multi objects) Classification In addition, Object Detection returns the coordinate of the Bounding Box and Confidence Score. Bounding Box It returns the t..

YOLO(You Only Look Once) 1. Devide the cell to the grid evenly 2. The grid cell which has the center of the object is assigned to detect that object(two red dots on the rightmost pic). 3. Each grid cell predict the bounding box and confidence score of bounding box. (Higher confidence score, thicker bounding box (The picture above (4)) ). 4. At the same time, classification is carried out simulta..