. Lclra, . Hclra, . Lchra, and . Hchra, 2 def extractTexture ( I , Z) : 2 def GANmean(A, m): 2 def centerrec ( I , selem=m.disk(1) ) : 2 def thinning

H. Points,

, For a few random points: 1. Show that the circularity of a disc is equal to 1. 2. Generate an array representing an object as a discrete disc

, Calculate its circularity and comment the results

, Convexity We want to know if the object X is convex. For that, we define the following measurement: conv(X) = A(X)

A. Ch,

, Compute the convex hull of a pattern from the Kimia database. 2. Evaluate the area of the filled convex hull

, Deduce the convexity of the pattern

, See ConvexHull from scipy . spatial . def feret_diameter ( I ) : 2

, Input : I binary image 8 def diagrams() : 2 name=

C. and P. , def getIndex (contour, point , connectivity ) : """ subfunction for getting the local direction 4 def Perimeter( fcode ) : 2 """ fcode : Freeman code 4

, perim = nb_diag * np. sqrt (2) + len ( fcode ) -nb_diag

, The perimeter is evaluated in the same way in skimage. Perimeter : 43.65685424949238 2 skimage

, # Definitions of the database , classes and images 2 rep = 'images_Kimia216

, =, vol.12

, # The features are manually computed properties = np.zeros (( nbClasses * nbImages

, 10 target = np.zeros (nbClasses * nbImages); index=0

, 12 for ind_c , c in enumerate( classes ) : filelist = glob . glob(rep+c+' * ' )

, 14 for filename in filelist : I = io . imread(filename )

, 16 prop = measure.regionprops( I )

, Classification We used a training set of 75% of the database and 25% for the test set. The scaler is used in order to rescale the data having different ranges and dimensions. Other scalers are proposed in sklearn . preprocessing. # percentage of the data used for splitting into train / test 2 percentTest, p.25

#. Mlp-classifier,

, # the data are first scaled propertiesMLP = StandardScaler () . fit_transform ( properties )

, Compute the distance between each pair of images in order to get a dissimilarity matrix

, Use the k-means algorithm to classify the images of the database into three classes (k = 3)

, See KMeans from sklearn . cluster

, Cite the names of the major image file formats and their main differences

, ? What is the difference with histogram stretching? ? From the mathematical definition of the derivative, explain the construction of the gradient operator

, Cite some method for contours detection, and list their pros and cons

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