typo correction and quiz

Author: onlyphantom

README.md

@@ -57,7 +57,7 @@ A math-first approach to learning computer vision in Python. The repository will
             - [Contour Retrieval and Approximation](edgedetect/edgedetect.html#contour-retrieval-and-approximation)
     - [Canny Edge Detector](edgedetect/edgedetect.html#canny-edge-detector)
         - [Edge Thinning](edgedetect/edgedetect.html#edge-thinning)
-        - [Hysterisis Thresholding](edgedetect/edgedetect.html#hysterisis-thresholding)
+        - [Hysteresis Thresholding](edgedetect/edgedetect.html#hysteresis-thresholding)
     - References and learn-by-building modules
 
 ## Future chapters

edgedetect/edgedetect.md

@@ -332,7 +332,7 @@ I said it's a multi-stage procedure, because the technique as described in his o
 2. Compute gradient magnitudes and angles
 3. Apply non-maximum suppression (NMS) 
     - Suppress close-by edges that are non-maximal, leaving only local maxima as edges
-4. Track edge by hysterisis
+4. Track edge by hysteresis
     - Suppress all other edges that are weak and not connected to strong edges and link the edges
 
 Step (1) and (2) in the procedure above can be achieved using code we've written so far in our Sobel Operator scripts. We use the Sobel mask filters to compute $G_x$ and $G_y$, respectively the gradient component in each orientation. We then compute the gradient magnitude and the angle $\theta$:
@@ -356,7 +356,7 @@ The output of step (3) is a binary image with thin edges.
 
 The code[^13] demonstrates how you would code such an NMS for the purpose of canny edge detection. 
 
-## Hysterisis Thresholding
+## Hysteresis Thresholding
 The final step of this multi-stage algorithm decides which among all edges are really edges and which of them are not. It accomplishes this using two threshold values, specified when we call the `cv2.Canny()` function:
 
 ```py

quiz.md

@@ -32,3 +32,14 @@
     - [ ] RETR_OUTER, CHAIN_APPROX_SIMPLE
     - [ ] RETR_OUTER, CHAIN_APPROX_NONE
     - [ ] RETR_LIST, CHAIN_APPROX_NONE
+
+6. The function call cv2.Canny(img, 50, 180) will determine which of the intensity gradients as definite edges?
+    - [ ] 40
+    - [ ] 100
+    - [ ] 200
+
+7. Which of the following is NOT part of the Canny Edge procedure?
+    - [ ] Compute gradient in each direction
+    - [ ] Suppress edges that are non-maximal
+    - [ ] Discard pixels that are more likely noise than true edges
+    - [ ] Retrieve only the extreme outer contours from the edges