scholarly journals DEVELOPMENT OF NOVEL ALGORITHM FOR HAAR TRANSFORM USING PAIRED TRANSFORM: IMPLEMENTATION ON TMS DSP PROCESSORS.

2020 ◽  
Vol 9 (6) ◽  
pp. 16-30
Keyword(s):  
Image Processing ◽  
Fast Algorithm ◽  
Mathematical Structure ◽  
The Novel ◽  
Haar Transform ◽  
Minimum Number ◽  
Hartley Transforms ◽  
Dsp Processors ◽  
Paired Transform ◽  
Novel Algorithm

Paired transform splits the mathematical structure of many discrete unitary transforms, including the Fourier, Hadamard, Cosine and Hartley transforms, into the minimum number of short transforms. The discrete Haar transform that is very useful in many signal and image processing applications can be also calculated by the fast paired transform. The Haar transform can be considered as the particular case of the paired transforms, namely the 2-paired transform. In this research a Novel Fast algorithm for Haar transform is developed using paired transform: Paired Fast Haar Transform (Paired FHT). For illustration purposes relation between the Haar and paired transforms are described using the examples for 16, 8, 4 – point transforms are analyzed in detail. Finally the novel Haar transform: Paired Fast Haar transform is implemented using Code Compose Studio for TMS DSP processor Starter Kit (TMS DSK) TMS 320 C 6713 DSP processor for understanding the possible sampling rates.

Developing an Inkjet Printer I: RGB Image to CMY Ink Amounts - Image Processing and Color Management

2020 ◽  
Vol 2020 (15) ◽  
pp. 350-1-350-10
Author(s):  
Yin Wang ◽  
Baekdu Choi ◽  
Davi He ◽  
Zillion Lin ◽  
George Chiu ◽  
...  
Keyword(s):  
Image Processing ◽  
Low Cost ◽  
Experimental Results ◽  
Color Management ◽  
Finger Nail ◽  
Inkjet Printer ◽  
Rgb Image ◽  
Novel Algorithm

In this paper, we will introduce a novel low-cost, small size, portable nail printer. The usage of this system is to print any desired pattern on a finger nail in just a few minutes. The detailed pre-processing procedures will be described in this paper. These include image processing to find the correct printing zone, and color management to match the patterns’ color. In each phase, a novel algorithm will be introduced to refine the result. The paper will state the mathematical principles behind each phase, and show the experimental results, which illustrate the algorithms’ capabilities to handle the task.

A Novel Algorithm to Detect a QPSK Signal with the Minimum Number of Samples

2015 ◽  
pp. 11-20
Author(s):  
Mohammed Saleh ◽  
Hilmi Sanusi ◽  
Adamu I. Abubakar ◽  
Haruna Chiroma ◽  
Edi Sutoyo ◽  
...  
Keyword(s):  
Minimum Number ◽  
Novel Algorithm

Novel Algorithmic Approach to Deciphering Rovash Inscriptions

2015 ◽  
pp. 7222-7233 ◽  
Author(s):  
Loránd Lehel Tóth ◽  
Raymond Pardede ◽  
Gábor Hosszú
Keyword(s):  
Experimental Results ◽  
The Novel ◽  
Statistical Probability ◽  
Algorithmic Approach ◽  
Topological Parameters ◽  
Novel Method ◽  
Novel Algorithm

The article presents a method to decipher Rovash inscriptions made by the Szekelys in the 15th-18th centuries. The difficulty of the deciphering work is that a large portion of the Rovash inscriptions contains incomplete words, calligraphic glyphs or grapheme errors. Based on the topological parameters of the undeciphered symbols registered in the database, the presented novel algorithm estimates the meaning of the inscriptions by the matching accuracies of the recognized graphemes and gives a statistical probability for deciphering. The developed algorithm was implemented in software, which also contains a built-in dictionary. Based on the dictionary, the novel method takes into account the context in identifying the meaning of the inscription. The proposed algorithm offers one or more words in a different random values as a result, from which users can select the relevant one. The article also presents experimental results, which demonstrate the efficiency of method.

scholarly journals Learning and Planning Based on Merged Experience from Multiple Situations for a Service Robot

2018 ◽  
Vol 8 (10) ◽  
pp. 1832
Author(s):  
Zhixian Chen ◽  
Baoliang Zhao ◽  
Shijia Zhao ◽  
Ying Hu ◽  
Jianwei Zhang
Keyword(s):  
Robot Learning ◽  
Physical Experiment ◽  
Planning Method ◽  
Service Robot ◽  
The Novel ◽  
Changing Environment ◽  
Task Knowledge ◽  
Learn Activity ◽  
Abstract Method ◽  
Novel Algorithm

For a service robot, learning appropriate behaviours to acquire task knowledge and deliberation in various situations is essential, but the existing methods do not support merging the plan-based activity experiences from multiple situations in the same task. In this paper, an abstract method is introduced to integrate the empirical activity schemas of multiple situations, and a novel algorithm is presented to learn activity schema with abstract methods. Furthermore, a novel planner called the schema-based optimized planner (SBOP) is developed based on the learned activity schema, in which actions merging optimization and partially backtracking techniques are adopted. A simulation with a PR2 robot and a physical experiment is conducted to validate the proposed method. The results show that the robot can generate a plan to recover from failure automatically using the novel learning and planning method, given that the experienced exception has been merged in the activity schema. Owing to the improved autonomy, the proposed SBOP exhibits increased efficiency in dealing with tasks containing loops and multiple activity schema instances. This research presents a novel solution of how to merge activity experiences from multiple situations and generate an intelligent and efficient plan that could adapt to a dynamically changing environment.

A Novel Neutrosophic Image Segmentation Based on Improved Fuzzy C-Means Algorithm (NIS-IFCM)

2019 ◽  
Vol 34 (05) ◽  
pp. 2055011
Author(s):  
Jing Zhao ◽  
Xiaoli Wang ◽  
Ming Li
Keyword(s):  
Computer Vision ◽  
Particle Swarm Optimization ◽  
Image Segmentation ◽  
Classical Problem ◽  
Local Optimum ◽  
The Novel ◽  
Swarm Optimization ◽  
Novel Method ◽  
Fuzzy C Means Algorithm ◽  
Novel Algorithm

Image segmentation is a classical problem in the field of computer vision. Fuzzy [Formula: see text]-means algorithm (FCM) is often used in image segmentation. However, when there is noise in the image, it easily falls into the local optimum, which results in poor image boundary segmentation effect. A novel method is proposed to solve this problem. In the proposed method, first, the image is transformed into a neutrosophic image. In order to improve the ability of global search, a combined FCM based on particle swarm optimization (PSO) is proposed. Finally, the proposed algorithm is applied to the neutrosophic image segmentation. The results of experiments show that the novel algorithm can eliminate image noise more effectively than the FCM algorithm, and make the boundary of the segmentation area clearer.

scholarly journals Tracking intermediate performance of vigilant attention using multiple eye metrics

SLEEP ◽  
2020 ◽  
Vol 43 (3) ◽  
Author(s):  
Takashi Abe ◽  
Kazuo Mishima ◽  
Shingo Kitamura ◽  
Akiko Hida ◽  
Yuichi Inoue ◽  
...  
Keyword(s):  
Sleep Deprivation ◽  
Human Error ◽  
Reaction Times ◽  
Simultaneous Recording ◽  
Time On Task ◽  
The Novel ◽  
Eyelid Closure ◽  
Psychomotor Vigilance Test ◽  
Falling Asleep ◽  
Novel Algorithm

Abstract Vigilance deficits account for a substantial number of accidents and errors. Current techniques to detect vigilance impairment measure only the most severe level evident in eyelid closure and falling asleep, which is often too late to avoid an accident or error. The present study sought to identify ocular biometrics of intermediate impairment of vigilance and develop a new technique that could detect a range of deficits in vigilant attention (VA). Sixteen healthy adults performed well-validated Psychomotor Vigilance Test (PVT) for tracking vigilance attention while undergoing simultaneous recording of eye metrics every 2 hours during 38 hours of continuous wakefulness. A novel marker was found that measured VA when the eyes were open—the prevalence of microsaccades. Notably, the prevalence of microsaccades decreased in response to sleep deprivation and time-on-task. In addition, a novel algorithm for detecting multilevel VA was developed, which estimated performance on the PVT by integrating the novel marker with other eye-related indices. The novel algorithm also tracked changes in intermediate level of VA (specific reaction times in the PVT, i.e. 300–500 ms) during prolonged time-on-task and sleep deprivation, which had not been tracked previously by conventional techniques. The implication of the findings is that this novel algorithm, named “eye-metrical estimation version of the PVT: PVT-E,” can be used to reduce human-error-related accidents caused by vigilance impairment even when its level is intermediate.

Accurate determination of DNA in agarose gels using the novel algorithm GelScann(1.0)

1995 ◽  
Vol 11 (2) ◽  
pp. 187-194
Author(s):  
Michael L. Metzker ◽  
Kyle M. Allain ◽  
Richard A. Gibbs
Keyword(s):  
Accurate Determination ◽  
The Novel ◽  
Agarose Gels ◽  
Novel Algorithm

Dynamic Controller Based on Ying Learning Algorithm for Medical Temperature System

2011 ◽  
Vol 187 ◽  
pp. 371-376
Author(s):  
Ping Zhang ◽  
Xiao Hong Hao ◽  
Heng Jie Li
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Fuzzy Neural Network ◽  
Learning Algorithm ◽  
Fuzzy Neural Networks ◽  
The Novel ◽  
Fuzzy Neural ◽  
Learning Set ◽  
And Training ◽  
Novel Algorithm

In order to avoid the over fitting and training and solve the knowledge extraction problem in fuzzy neural networks system. Ying Learning Dynamic Fuzzy Neural Network (YL-DFNN) algorithm is proposed. The Learning Set based on K-VNN is constituted from message. Then the framework of is designed and its stability is proved. Finally, Simulation indicates that the novel algorithm is fast, compact, and capable in generalization.

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