Image compression using HAAR discrete wavelet transform

Kanagaraj, Hemalatha; Muneeswaran, V.

doi:10.1109/icdcs48716.2020.243596

Cited by 37 publications

(12 citation statements)

References 2 publications

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“…Because DWT can analyze frequencies in the time domain, it has been regarded as a promising method for real-time sensor applications [ 39 , 40 ]. In this study, we adopted 2nd level Haar DWT for slip detection [ 41 ], and further details are explained in Section 3.2 . Moreover, setting a threshold is necessary for decoupling slip, so we set the threshold to be three times the standard deviation of the noise on the basis of the three-sigma rule.…”

Section: Working Principle and Fundamental Characterizationmentioning

confidence: 99%

BaroTac: Barometric Three-Axis Tactile Sensor with Slip Detection Capability

Kim

Hwang

2022

Sensors

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Tactile sensors for robotic applications enhance the performance of robotic end-effectors as they ca n provide tactile information to operate various tasks. In particular, tactile sensors can measure multi-axial force and detect slip can aid the end-effectors in grasping diverse objects in an unstructured environment. We propose BaroTac, which measures three-axial forces and detects slip with a barometric pressure sensor chip (BPSC) for robotic applications. A BPSC is an off-the-shelf commercial sensor that is inexpensive, easy to customize, robust, and simple to use. While a single BPSC-based tactile sensor can measure pressure, an array of BPSC-based tactile sensors can measure multi-axial force through the reactivity of each sensor and detect slip by observing high frequency due to slip vibration. We first experiment with defining the fundamental characteristics of a single-cell BPSC-based sensor to set the design parameters of our proposed sensor. Thereafter, we suggest the sensing method of BaroTac: calibration matrix for three-axis force measurement and discrete wavelet transform (DWT) for slip detection. Subsequently, we validate the three-axis force measuring ability and slip detectability of the fabricated multi-cell BPSC-based tactile sensor. The sensor measures three-axis force with low error (0.14, 0.18, and 0.3% in the X-, Y- and Z-axis, respectively) and discriminates slip in the high-frequency range (75–150 Hz). We finally show the practical applicability of BaroTac by installing them on the commercial robotic gripper and controlling the gripper to grasp common objects based on our sensor feedback.

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Section: Working Principle and Fundamental Characterizationmentioning

confidence: 99%

BaroTac: Barometric Three-Axis Tactile Sensor with Slip Detection Capability

Kim

Hwang

2022

Sensors

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“…As an illustration, the PSNR and compression ratio (CR) of the Lena image achieved by the proposed approach simulation were 42.4094 dB and 47.5435, respectively. In [10] for effective and economical image compression, the discrete wavelet transforms (DWT) based on HAAR wavelets is used. Since the coefficient of HAAR DWT is either 1, or -1, it offers a simple method of compression.…”

Section: Image Compression With Waveletmentioning

confidence: 99%

Images Compression using Combined Scheme of Transform Coding

Ahmed¹,

George²,

Hadi³

2022

J. Engg. Res. & Sci.

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Some problems want to be solved in image compression to make the process workable and more efficient. Much work had been done in the field of lossy image compression based on wavelet and Discrete Cosine Transform (DCT). In this paper, an efficient image compression scheme is proposed, based on a common encoding transform scheme; It consists of the following steps: 1) biorthogonal (tab 9/7) wavelet transform to split the image data into sub-bands, 2) DCT to de-correlate the data, 3) the combined transform stage's output is subjected to scalar quantization before being mapped to positive, 4) and LZW encoding to produce the compressed data. The peak signal-to-noise (PSNR), compression ratio (CR), and compression gain (CG) measures were used to perform a comparative analysis of the performance of the whole system. Several image test samples were used to test the performance behavior. The simulation results show the efficiency of these combined transformations when LZW is used in the field of data compression. Compression outcomes are encouraging and display a significant reduction in image file size at good resolution.

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“…The motivation for using this transformation is due to its co-linear properties and the fact that it remains in the Affine space after the transformation. Also, a wavelet-based single level decomposition [29] as a low-pass filter and Gaussian noise [30] for noise contamination in the images were considered for augmentation.…”

Section: A Pre-processingmentioning

confidence: 99%

“…Wavelet decomposition Here single level decomposition of the discrete Haar wavelet [29] was considered for decomposing the images and retained with approximation level. The sample images from the developed dataset are presented in Fig.…”

Section: A Pre-processingmentioning

confidence: 99%

Movie Title Extraction and Script Separation Using Shallow Convolution Neural Network

et al. 2021

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Graphical texts in natural images play an important role in portraying information in multitudinous fields such as communication, education, and entertainment to name a few. Recognizing text in scene images is challenging due to the inherent complexity of the images. Text recognition in natural images involves script identification, which requires text localization. This is not trivial for natural scene images due to the presence of disparate foreground/background components. For scene images like movie posters, the challenge is more dominant. The challenges aggravate due to the presence of composite characteristics of posters like complex graphics background and the presence of different texts like a movie title, names of actors, producers, directors, and tagline. These texts have miscellaneous fonts, variations in colors, size, orientation, and textures. In this work, an M-EAST (modified EAST) model is proposed, which is based on the EAST (efficient and accurate scene text detector) model for text localization. A novel movie title extraction is thereafter used for separating the title from the extracted text pool. Finally, the title script was identified using a shallow convolutional neural network (SCNN)-based to ensure functionality in low-resource environments. Experiments were performed on a dataset of movieposter images of Tollywood, Bollywood, and Hollywood industries, and a highest accuracy of 99.82% was obtained. The system performed better than the reported techniques.

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Image compression using HAAR discrete wavelet transform

Cited by 37 publications

References 2 publications

BaroTac: Barometric Three-Axis Tactile Sensor with Slip Detection Capability

BaroTac: Barometric Three-Axis Tactile Sensor with Slip Detection Capability

Images Compression using Combined Scheme of Transform Coding

Movie Title Extraction and Script Separation Using Shallow Convolution Neural Network

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