Image segmentation on a quantum computer

Caraiman, Simona; Manta, Vasile

doi:10.1007/s11128-015-0932-1

Cited by 90 publications

(34 citation statements)

References 45 publications

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“…A quantum version of the image segmentation algorithm is developed [8] using thresholding-based operations. This work analyzed the applications of quantum image processing and prove their efficiency than classical approaches.…”

Section: Literature Reviewmentioning

confidence: 99%

Quantum-Assisted Retinal Drusen Detection Algorithm using Entropy Based Image Processing Techniques

Durai,

Vijayakumar

2020

IJEAT

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Drusen identification is the fundamental operation in the automated diagnosis of eye diseases. Manual and automatic detection of the drusen in the retinal fundus images has been developed recently in the classical manner only. This work provides the quantum-based retinal drusen detection method using entropy-based image processing techniques. This algorithm is the composite system of two channels, classical and quantum channels for the preprocessing and drusen detection respectively. This research work has been evaluated with the databases of DRIVE, STARE, MESSIDOR, E-Optha-Ex and ONH-Hunter. This quantum-based approach will be analyzed with the results of the existing classical methods and proves its efficiency from the calculations of sensitivity, specificity, accuracy and execution time.

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Section: Literature Reviewmentioning

confidence: 99%

Quantum-Assisted Retinal Drusen Detection Algorithm using Entropy Based Image Processing Techniques

Durai,

Vijayakumar

2020

IJEAT

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“…A larger class of more complex image processing operations can be applied using this model. Compared to the FRQI color representation mode, this approach requires m qubits to represent L=2 m color values instead of one color qubit [31] [36]. Similar to FRQI model, there is another model which encodes the color information in the probability amplitudes of the one qubit state.This probability amplitude can be measured by the bijective relationship between the frequency of the monochromatic electromagnetic wave (describes the color) and the angle parameter of a qubit.The same model is applied to infrared images where the injective function is used to measure probability amplitude of the corresponding one qubit state [38].…”

Section: Caraiman's Quantum Image Representation Model (Cqir)mentioning

confidence: 99%

“…It is a time consuming and expensive procedure. The above model which requires one qubit to represent color information of a pixel is superior than the model of the paper [31], requires m qubits to represent 2 m color values. But both models are not using the basic simple quantum gates and multi-valued quantum computing logic which leads to the simple representation of specially RGB color images.…”

Section: Caraiman's Quantum Image Representation Model (Cqir)mentioning

confidence: 99%

Quantum image processing: challenges and future research issues

Chakraborty

Mandal

Shaikh

2018

Int. j. inf. tecnol.

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Image processing on quantum platform is a hot topic for researchers now a day. Inspired from the idea of quantum physics, researchers are trying to shift their focus from classical image processing towards quantum image processing.This paper starts with a brief review of the principles which underlie quantum computing, and also deals with some of the basics of qubits and quantum computing.Then this paper starts to deal with some different methods of image storage, representation and retrieval in a quantum system.This paper also describes the advantages of using those methods in quantum systems compare to classical systems. In the next section, a short discussion on some of the important aspects, comparison among them and applications of quantum image processing is presented. A few other hot topics and open problems in quantum image processing are mentioned in this paper. This review article will provide the readership an overview of progress witnessed in the area of Quantum Image processing while also simulating further interest to pursue more advanced research in it.

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“…So various quantum representations have been proposed, such as, Qubit Lattice [3], entangled image [4], real ket [5], flexible representation of quantum images (FRQI) [6], a novel enhanced quantum representation of digital images (NEQR) [7], multichannel representation for quantum images (MCRQI) [8], a normal arbitrary quantum superposition state (NAQSS) [9], and a novel quantum representation for color digital images (NCQI) [10]. Secondly, many kinds of quantum image processing algorithms were developed, such as geometric transformations [11,12], image translation [13][14][15], image scaling [16][17][18], image scrambling [19][20][21], image segmentation [22], feature extraction [23], edge detection [24], and image matching [25,26].…”

Section: Introductionmentioning

confidence: 99%

A Novel Quantum Steganography Scheme Based on ASCII

Zhou¹,

Luo²

2020

Advances in Quantum Communication and Information

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Based on the novel enhanced quantum representation for quantum image (NEQR), a new blind quantum steganography scheme is proposed. In this scheme, an improved quantum representation of text utilizing ASCII is provided that uses two qubit sequences to store the same quantum text message. The general embedding process of the scheme is as follows: firstly, the cover image of sized 2 n Â 2 n will be divided into eight blocks of sized 2 nÀ2 Â 2 nÀ1 , and the secret quantum text of sized 2 nÀ2 Â 2 nÀ1 is scrambled by Gray code transform method. Then, the disorder quantum text is embedded into the eight blocks of cover image employing the Gray code as a judgment condition. Meanwhile, the corresponding quantum circuits are drawn. Through the analysis of all quantum circuits, it can be concluded that the scheme has a lower complexity, that is, O(n). And the performance of the proposed scheme is analyzing in terms of simulation results of three items: visual quality, circuit complexity, and robustness.

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Image segmentation on a quantum computer

Cited by 90 publications

References 45 publications

Quantum-Assisted Retinal Drusen Detection Algorithm using Entropy Based Image Processing Techniques

Quantum-Assisted Retinal Drusen Detection Algorithm using Entropy Based Image Processing Techniques

Quantum image processing: challenges and future research issues

A Novel Quantum Steganography Scheme Based on ASCII

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