Edge detection algorithm based on quantum superposition principle and photons arrival probability

Abstract

The detection of object edges in images is a crucial step employed in a vast amount of computer vision applications, for which a series of different algorithms has been developed in the last decades. This paper proposes a new edge detection method based on quantum information, which is achieved in two main steps: (i) an image enhancement stage that employs the quantum superposition law and (ii) an edge detection stage based on the probability of photon arrival to the camera sensor. The proposed method has been tested on synthetic and real images devoted to agriculture applications, where Fram & Deutsh criterion has been adopted to evaluate its performance. The results show that the proposed method gives better results in terms of detection quality and computation time compared to classical edge detection algorithms such as Sobel, Kayyali, Canny and a more recent algorithm based on Shannon entropy.

Edge detection algorithm for omnidirectional images, based on superposition laws on Blach’s sphere and quantum entropy

“…Then, we apply equations 9 and 12 for each subsystem of three pixels, an example for the 90° direction is given in the Table 1, where the state '0' and '1' represent a background and an object pixel respectively. By definition, an edge point (edge pixel) is defined as an object pixel that have at least one background pixel in its neighborhood [26], so this two cases can be ignored:…”

Algorithm for Iris recognition based on contourlet Transform and Entropy

“…The main motivation of using this technique is that the eyelashes are typically almost vertically aligned on an hyperbolic shape, so we can take only the vertical gradient points (instead of the original gray scale image) with the hyperbolic HT which has less parameters than other techniques presented for the same purpose, hence reducing the effect of the eyelids and the eyelashes when applying the circular Hough transform for iris segmentation, while reducing at the same time the processing cost of the system [11], as shown in Figure 4. Next, once the non-relevant parts of the image have been deleted, we deal with the iris segmentation process through a combination of (i) an edge detection algorithm based on the quantum superposition law, that we proposed in [30], which achieves better performance than other edge detectors in terms of edge continuity even with the presence of noise, and (ii) the circular Hough Transform [31]. This combined process yields the center position (a,b) and the radius r of both the pupil and the iris.…”

“…This model also takes into consideration the pupil dilation in order to give a constant normalized iris. Finally, in order to take into account only the information from the iris, the black areas of the normalized image are discarded, while the iris region goes through an enhancement process using the method based on the quantum superposition law that we presented in [30]. This corrects the illumination irregularities and enhances the intensity discontinuities, which will be useful for the generation of the iris descriptor from.…”

Performance parameters optimization of CMOS analog signal processing circuits based on smart algorithms

“…The two main types of integrated circuits (IC) implementation are bipolar and complementary metal oxide semiconductor (CMOS) [1]. In comparison to CMOS technology, bipolar technology is known for having lower noise, better performance at high frequencies, and greater transconductance [2], [3]. Bipolar technology is better than CMOS technology because it has a higher input resistance, uses less power, and can be made on a smaller area of silicon [4].…”

“…The OTA with a single input and a single output, OTA with a differential input, and OTA with a balanced input and differential output [15], [16]. In addition, the current mode technique offers more potential, a wider dynamic range, a simpler circuit design, the lowest power consumption, and a wider signal bandwidth than the voltage mode approach, owing towards its enhanced linearity (bipolar and CMOS technologies) to establish the existing transport circuits [3], [4].…”