Low complexity and efficient architecture of 1D-DCT based Cordic-Loeffler for wireless endoscopy capsule

Jarray, Nedra; Elhaji, Majdi; Zitouni, Abdelkrim

doi:10.1109/ssd.2015.7348130

Cited by 6 publications

(1 citation statement)

References 20 publications

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“…In [41], an FPGA implementation of data processing core with a focus on image compression for WCE device is presented. In [42], a low complexity architecture for one-dimensional discrete cosine transform (DCT) transform is presented. In [43], concerning low-resolution and properties of WCE images, specific patterns in different image channels are extracted for DPCM coding and are utilized for better compression.…”

mentioning

confidence: 99%

Multiple abnormality detection for automatic medical image diagnosis using bifurcated convolutional neural network

Hajabdollahi

Esfandiarpoor

Sabeti

et al. 2020

Biomedical Signal Processing and Control

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mentioning

confidence: 99%

Multiple abnormality detection for automatic medical image diagnosis using bifurcated convolutional neural network

Hajabdollahi

Esfandiarpoor

Sabeti

et al. 2020

Biomedical Signal Processing and Control

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Low-power DCT-based compressor for wireless capsule endoscopy

Shabani

Timarchi

2017

Signal Processing: Image Communication

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Hardware image assessment for wireless endoscopy capsules

Khorsandi

Karimi

Samavi

et al. 2016

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Wireless capsule endoscopy is a new technology in the realm of telemedicine that has many advantages over the traditional endoscopy systems. Transmitted images should help diagnosis of diseases of the gastrointestinal tract. Two important technical challenges for the manufacturers of these capsules are power consumption and size of the circuitry. Also, the system must be fast enough for real-time processing of image or video data. To solve this problem, many hardware designs have been proposed for implementation of the image processing unit. In this paper we propose an architecture that could be used for the assessment of endoscopy images. The assessment allows avoidance of transmission of medically useless images. Hence, volume of data is reduced for more efficient transmission of images by the endoscopy capsule. This is done by color space conversion and moment calculation of images captured by the capsule. The inputs of the proposed architecture are RGB image frames and the outputs are images with converted colors and calculated image moments. Experimental results indicate that the proposed architecture has low complexity and is appropriate for a real-time application.

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Low complexity and efficient architecture of 1D-DCT based Cordic-Loeffler for wireless endoscopy capsule

Cited by 6 publications

References 20 publications

Multiple abnormality detection for automatic medical image diagnosis using bifurcated convolutional neural network

Multiple abnormality detection for automatic medical image diagnosis using bifurcated convolutional neural network

Low-power DCT-based compressor for wireless capsule endoscopy

Hardware image assessment for wireless endoscopy capsules

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