Shape ellipticity from Hu moment invariants

Combination of Dominant Color Descriptor and Hu Moments in Consistent Zone for Content Based Image Retrieval

“…An algorithm of image recognition techniques, including Hu invariant moment, texture features, lateral Fourier transform and Daubechies (DBn) wavelet transform, was used to describe the features of defects of sewer pipe [20]. In paper [21], an explicit formula was derived which uses the first two Hu moment invariants to compute a shape ellipticity measure, i.e. to evaluate how much a planar shape differs from an ellipse.…”

“…Use equations ( 15)- (20) to calculate the average precision and recall rate. And use equation (21) to calculate the Fmeasure. The retrieval results of different algorithms on the Corel-5k database such as precision, recall, PR curve and Fmeasure curve are shown in Figure 6.…”

Ellipticity and Circularity Measuring via Kullback–Leibler Divergence

“…The work presented in this article aims to partially generalize the methods presented by Žunić et al in work [31], Žunić and Žunić in [30], and Rosin in [24] which describe circularity and ellipticity measures. The reason to choose these methods is their performance superiority in the case of shape boundary defects compared to the other standard methods, namely, the behavior of these measures (i.e., numerical shape characteristics) can be relatively easily understood and their behavior can be reasonably predicted.…”

“…measure of ellipticity and circularity. Our measures were tested on several examples from [30,31]. Experiments verify many advantages of our approach, e.g., behavior consistent with the human intuition and its invariance in similarity transformation.…”

“…We highlight that the values of C st and C H were taken from [31], while E H was taken from [30]. Moreover, the values of C 2 and C H are theoretically equal-compare with Observation 1-the differences are caused by a numerical …”