A high speed roller dung beetles clustering algorithm and its architecture for real-time image segmentation

Ratnakumar, Rahul; Nanda, Satyasai Jagannath

doi:10.1007/s10489-020-02067-7

Cited by 13 publications

(6 citation statements)

References 54 publications

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“…e corresponding research institutions in Europe mainly use collaborative information to improve the corresponding collaborative filtering algorithm, which can enhance the recommendation effect through the corresponding collaborative information. At the level of the corresponding recommendation algorithm, the main consideration and research direction focus on the sparsity of collected data, the cold start of the system, the scalability of the system, and the robustness of the system [20][21][22][23].…”

Section: Analysis Of Research Status Of Pitch Control Software Infras...mentioning

confidence: 99%

Design of Pitch Control Software Infrastructure Based on Collaborative Filtering Algorithm

Roongruang

2022

Scientific Programming

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The pitch control of electronic equipment is the overall and key problem of electronic equipment system. The traditional pitch control of electronic equipment mainly depends on the volume control table, but this method depends too much on the hardware design, the corresponding pitch control effect is relatively unstable, and the cost is high. Based on the research of traditional pitch control software, this project improves the collaborative filtering algorithm and reduces the range of nearest neighbour set of pitch samples by introducing clustering algorithm, to further shorten the search time of neighbour set and finally improve the real time and scalability of the system. To adapt to the environment and user preferences, this study proposes to calculate the attributes between different items when improving the collaborative filtering algorithm, so as to further determine the unique attributes between items and determine the similarity between items, so as to introduce the pitch preference correction factor based on user attributes, so as to realize the high precision of electronic equipment based on pitch control software preference recommendation setting. Based on this, this project takes the improved collaborative filtering algorithm as the core algorithm to build a set of digital TV pitch control software system and realizes the verification of the algorithm proposed in this study based on MATLAB simulation software. The experimental results show that the pitch control accuracy of the algorithm is about 10% higher than that of the traditional algorithm. In terms of the intelligence of the corresponding algorithm, the algorithm proposed in this study has obvious advantages compared with the traditional algorithm. At the same time, its intelligent recommendation to users also has high intelligence, and the corresponding intelligent recommendation rate is about 4%–10% higher than that of the traditional algorithm, which proves that the algorithm in this study has obvious advantages.

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Section: Analysis Of Research Status Of Pitch Control Software Infras...mentioning

confidence: 99%

Design of Pitch Control Software Infrastructure Based on Collaborative Filtering Algorithm

Roongruang

2022

Scientific Programming

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“…The FSM dealing with this architecture composed of a Moore machine with 15 stages. 39 Here, all the data bus lines composed of data‐bus with a width of 32‐bits. Initially, the histogram analyzer will accept the image data and calculates the possible number of centroids or clusters for the same image.…”

Section: Proposed Architecture For Automatic Image Segmentationmentioning

confidence: 99%

“… 36 FPGAs can be used to accelerate real‐time image segmentation problems by employing digital signal processing simplification techniques. The FSM dealing with this architecture composed of a Moore machine with 15 stages 39 . Here, all the data bus lines composed of data‐bus with a width of 32‐bits.…”

Section: Proposed Architecture For Automatic Image Segmentationmentioning

confidence: 99%

A high‐speed unsupervised hardware architecture for rapid diagnosis of COVID‐19

Ratnakumar

Nanda

2022

Circuit Theory & Apps

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Summary In the diagnosis of COVID‐19, investigation, analysis, and automatic counting of blood cell clusters are the most essential steps. Currently employed methods for cell segmentation, identification, and counting are time‐consuming and sometimes performed manually from sampled blood smears, which is hard and needs the support of an expert laboratory technician. The conventional method for the blood‐count‐test is by automatic hematology analyzer which is quite expensive and slow. Moreover, most of the unsupervised learning techniques currently available presume the medical practitioner to have a prior knowledge regarding the number and action of possible segments within the image before applying recognition. This assumption fails most often as the severity of the disease gets increased like the advanced stages of COVID‐19, lung cancer etc. In this manuscript, a simplified automatic histopathological image analysis technique and its hardware architecture suited for blind segmentation, cell counting, and retrieving the cell parameters like radii, area, and perimeter has been identified not only to speed up but also to ease the process of diagnosis as well as prognosis of COVID‐19. This is achieved by combining three algorithms: the K‐means algorithm, a novel statistical analysis technique‐HIST (histogram separation technique), and an islanding method an improved version of CCA algorithm/blob detection technique. The proposed method is applied to 15 chronic respiratory disease cases of COVID‐19 taken from high profile hospital databases. The output in terms of quantitative parameters like PSNR, SSIM, and qualitative analysis clearly reveals the usefulness of this technique in quick cytological evaluation. The proposed high‐speed and low‐cost architecture gives promising results in terms of performance of 190 MHz clock frequency, which is two times faster than its software implementation.

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“…ousands of kinds of image segmentation algorithms have been proposed, and new image segmentation algorithms are constantly being born. Common image segmentation methods include threshold-based segmentation methods, edge-based segmentation methods, and region-based segmentation methods [8][9][10][11][12][13]. In recent years, Bo et al [14] proposed a new deformable contour model for ultrasonic image sequence segmentation, which can resist the in uence of misleading or weak boundary in ultrasonic image segmentation.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of Local Threshold Segmentation Based on FPGA

Gao

Wang

Chen

et al. 2022

Journal of Electrical and Computer Engineering

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In the process of the development of image processing technology, image segmentation is a very important image processing technology in the field of machine vision, pedestrian detection, medical imaging, and so on. However, the traditional image segmentation technology cannot solve the problems of reflection and uneven illumination. This paper presents a local threshold segmentation method based on FPGA, which can automatically select the optimal threshold according to different gray levels of images. First, the image is processed by mean filtering to remove noise interference in the image. Then, the idea of the mean value of the local neighborhood block and the Gaussian weighted sum in the local neighborhood is used to deal with the reflective and uneven light on the image. The process is designed and realized on FPGA. Finally, the design algorithm is verified by ModelSim simulation software and QT5 software. The experimental results show that the algorithm can effectively solve the problems of reflection and uneven illumination on the image surface, and the segmentation effect is significantly improved compared with the fixed threshold algorithm and Otsu algorithm. It also has certain reference value in medicine, agriculture, engineering, and other fields.

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A high speed roller dung beetles clustering algorithm and its architecture for real-time image segmentation

Cited by 13 publications

References 54 publications

Design of Pitch Control Software Infrastructure Based on Collaborative Filtering Algorithm

Design of Pitch Control Software Infrastructure Based on Collaborative Filtering Algorithm

A high‐speed unsupervised hardware architecture for rapid diagnosis of COVID‐19

Design and Implementation of Local Threshold Segmentation Based on FPGA

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