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Adaptive Hint Propagation for Iterative Stereo Matching

Adaptive Hint Propagation for Iterative Stereo Matching

引用

IEEE visual communications and image processing (VCIP)

作者： Anning Hu Ang Li Danping Zou Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331529543

ISBN: (纸本)9798331529550

While sparse depth hints from LiDAR points have been utilized as guidance to enhance stereo matching, the improvement is hindered by the low density and uneven distribution of those points. To deal with these challenges, the sparse LiDAR hints are usually expanded for further processing. However, existing methods use only the local information of a fixed window surrounding the sparse hint, leading to inaccurate propagation that ultimately deteriorates stereo matching results. We introduce a new adaptive LiDAR propagation recurrent network by incorporating global context and local information, propagating the hints with an adaptive deformable window, and iteratively updating a disparity field through a recurrent unit. We have conducted comprehensive experiments on various public datasets. The results show that our method produces better matching quality than existing methods.

关键词： Adaptive systems Laser radar Costs visual communication image processing Iterative methods

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image Data Hiding in Neural Compressed Latent Representations

Image Data Hiding in Neural Compressed Latent Representation...

引用

IEEE visual communications and image processing (VCIP)

作者： Chen-Hsiu Huang Ja-Ling Wu Dept. of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

We propose an end-to-end learned image data hiding framework that embeds and extracts secrets in the latent representations of a generic neural compressor. By leveraging a perceptual loss function in conjunction with our proposed message encoder and decoder, our approach simultaneously achieves high image quality and high bit accuracy. Compared to existing techniques, our framework offers superior image secrecy and competitive watermarking robustness in the compressed domain while accelerating the embedding speed by over 50 times. These results demonstrate the potential of combining data hiding techniques and neural compression and offer new insights into developing neural compression techniques and their applications.

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image Text-to-Speech Converter with Desired Language Translation 7

Image Text-to-Speech Converter with Desired Language Transla...

引用

2023 7th International conference On Computing, Communication, Control And Automation, ICCUBEA 2023

作者： Singh, Arshdeep Ramandeep Sonker, Akansha Vanshika Moghe, Shreyash Munjal, Meenakshi Chandigarh University Department of Computer Science and Engineering Mohali India Chandigarh University Department of Electronics & Communications Engineering Mohali India

ISBN: (纸本)9798350304268

Pictorial data is the most expressive representation of an information using the graphics and designs. Mostly pictorial text data which is needed by the user are unable to access due to a language barrier (pictorial data may be in a different language) or because the image itself prevents to doing so. On platforms like the internet or social media, millions of photographs are shared with billions of written sentences. The issue arises when a person finds an image on the internet that contains text data but, in a language, they are unfamiliar with. Presentations are crucial in the corporate world for expressing concepts through visual information. When dealing with people from different cultures, a language barrier is likely to arise. This is significant on a worldwide scale. image text translation is desperately needed there. It takes a lot of effort and human capacity to address this problem manually by utilizing books and dictionaries. There are numerous websites and businesses on the internet that are active and offering the service of image text translation in speech form as a solution to this issue. Not just for this, but also when there is account case of a user who is blind and speaks a foreign culture's language and is unable to translate any pictorial text data. There, the issue of speech conversion and translation also surfaces. Many social media platforms are working to implement the speech recognition and translation of pictorial data so that it is simple to share the information with every user of their platform. © 2023 IEEE.

关键词： image pre-processing Optical Character Recognition (OCR) Speech Synthesis Text-to-Speech (TTS)

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LMM-driven Semantic image-Text Coding for Ultra Low-bitrate Learned image Compression

LMM-driven Semantic Image-Text Coding for Ultra Low-bitrate ...

引用

IEEE visual communications and image processing (VCIP)

作者： Shimon Murai Heming Sun Jiro Katto School of Fundamental Science and Engineering Waseda University Tokyo Japan Faculty of Engineering Yokohama National University Japan

ISBN: (数字)9798331529543

ISBN: (纸本)9798331529550

Supported by powerful generative models, low-bitrate learned image compression (LIC) models utilizing perceptual metrics have become feasible. Some of the most advanced models achieve high compression rates and superior perceptual quality by using image captions as sub-information. This paper demonstrates that using a large multi-modal model (LMM), it is possible to generate captions and compress them within a single model. We also propose a novel semantic-perceptual-oriented fine-tuning method applicable to any LIC network, resulting in a 41.58% improvement in LPIPS BD-rate compared to existing methods. Our implementation and pre-trained weights are available at https://***/tokkiwa/imageTextCoding.

关键词： Measurement image coding visual communication Semantics Rate-distortion Diffusion models

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Multi-GRU Based Automated image Captioning for Smartphones 29

Multi-GRU Based Automated Image Captioning for Smartphones

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29th IEEE conference on Signal processing and communications Applications (SIU)

作者： Keskin, Rumeysa Moral, Ozge Taylan Kilic, Volkan Onan, Aytug Izmir Katip Celebi Univ Dept Elect & Elect Engn Izmir Turkey Izmir Katip Celebi Univ Dept Comp Engn Izmir Turkey

ISBN: (纸本)9781665436496

image captioning is the description of an image with natural language expressions using computer vision and natural language processing fields. Recent advances in hardware and processing power in smartphones lead the development of many image captioning applications. In this study, a novel automatic image captioning system based on the encoder-decoder approach that can be applied in smartphones is proposed. While high-level visual information is extracted with the ResNet152V2 convolutional neural network in the encoder part, the proposed decoder transforms the extracted visual information into natural expressions of the images. The proposed decoder with the multilayer gated recurrent unit structure allows generating more meaningful captions using the most relevant visual information. The proposed system has been evaluated using different performance metrics on the MSCOCO dataset and it outperforms the state-of-the-art approaches. The proposed system is also integrated with our custom-designed Android application, named IMECA, which generates captions in offline mode unlike similar applications. Thus, image captioning is intended to be practical for more people.

关键词： image captioning computer vision natural language processing Android application

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Skin Disease Detection Using Saliency Maps and Segmentation Techniques 7th

Skin Disease Detection Using Saliency Maps and Segmentation ...

引用

7th International conference on Computer Vision and image processing, CVIP 2022

作者： Toteja, Rishit Gupta, Dhruv Gautam, Vibhor Vishwakarma, Dinesh Kumar Delhi Technological University Shahbad Daulatpur Main Bawana Road Delhi110042 India

ISBN: (纸本)9783031314063

Skin diseases are the most common disease on the planet. When detecting skin diseases, dermatologists must have a high degree of expertise and precision, which is why computer-aided diagnosis is so helpful. An approach for detecting skin diseases has been presented to give more information. Several investigations have been carried out to aid in diagnosing skin disorders such as skin cancer and skin tumours. However, exact identification of skin disease is challenging to cure because of the following factors: visual likeness, little contrast in-between the lesions and skin that is between the affected and non-diseased areas, etc. In this paper we propose a model that uses an image set which is pre-processed by various techniques like deblurring, noise reduction, and then enhanced. The images are then segmented using U-Net and MobileNetV2 is used for classification. The disease is detected at the output for a corresponding input image based on the definite pattern pertaining to a dispersant in the processed image. Then, we compute a class saliency map for the provided image and class. We demonstrate how ConvNets may classify and segment skin diseases using such maps. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： image segmentation

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Spatial Domain Method for image Analysis: A Grey-Level Computation Approach 7th

Spatial Domain Method for Image Analysis: A Grey-Level Compu...

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Proceedings of the 7th International conference on Advances in Computing and Data Sciences, ICACDS 2023

作者： Deepika, Kumari Punj, Deepika Jyoti Atur Centre Model Colony Pune411016 India J C Bose University of Science and Technology 6 Mathura Rd Sector 6 Haryana Faridabad121006 India

ISBN: (纸本)9783031379390

This paper discusses image enhancement, which involves adjusting captured images to improve their visual quality and suitability for display or analysis using techniques like filtering, histogram equalization, and contrast adjustment. The spatial domain method is used for manipulating image grey levels, and the study analyses the transformed images using BRIQUE, NIQE, and PIQE quality metric descriptors. The study shows that the type of image used for processing depends on the application, and binary images have the highest PIQE score. Power law transformation or Gamma-corrected images can reduce or enhance contrast, depending on the gamma’s value. The transformed images have different scores based on the quality metric used. The study also finds that the sum of the global threshold values of an input image and its inverse is 1, and the scores for binary images using both thresholds are similar. Finally, the study shows that BRISQUE and PIQE scores are higher for gamma and more significant than 1;NIQE scores are similar for both gamma values. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： image enhancement

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Mono+Sub: Compressing Light Field as Monocular image and Subsidiary Data

Mono+Sub: Compressing Light Field as Monocular Image and Sub...

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IEEE visual communications and image processing (VCIP)

作者： Ryosuke Imazu Chihiro Tsutake Keita Takahashi Toshiaki Fujii Nagoya University Japan

ISBN: (数字)9798331529543

ISBN: (纸本)9798331529550

A light field is usually represented as a set of multi-view images captured from a two-dimensional (2-D) array of viewpoints and requires a large amount of data compared with a standard 2-D image. We propose a 2-D compatible light-field compression method for encoding a light field as a 2-D monocular image and subsidiary data. In terms of the image quality, we prioritize the central image (regarded as the 2-D monocular image) over the other images in the light field, because the light field is considered an extension of the 2-D monocular image. To this end, we encode and decode the monocular image using a standard image codec and introduce a learned encoder and decoder pair for the subsidiary data. Experimental results indicate that our method achieved promising rate-distortion performance, especially for extremely low bit-rate ranges. Even though our method requires only a small amount of subsidiary data compared with those for the monocular image, the entire light field can be reconstructed with reasonable visual quality.

关键词： visualization image coding visual communication Two-dimensional displays Scalability Rate-distortion Network architecture Light fields Standards Optimization

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Comparison of the State-of-the-Art image and Video Quality Assessment Metrics 29

Comparison of the State-of-the-Art Image and Video Quality A...

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29th IEEE conference on Signal processing and communications Applications (SIU)

作者： Akkaya, Emre Ozbek, Nukhet Ege Univ Muhendislik Fak Elekt Elekt Muhendisligi Bolumu Izmir Turkey

ISBN: (纸本)9781665436496

Today, thanks to the developing technology, changes are experienced in many areas and these changes sometimes bring some problems, issues that need to be solved or improved. In the field of digital image and video processing, the viewer experience has been greatly improved with the development of image and video coding methods and technologies in recent years. However, due to these developments, the importance of video and image quality evaluation techniques has increased. In the field of imaging technology, although the human visual system and human judgment experiments will give us the most accurate results, this rapidly growing field has made human judgment experiments unsuitable with the increasing content. At this point, effective and automatic quality assessment metrics are needed to evaluate and optimize advanced compression technologies in terms of visual perception quality. In this paper, our aim is to compare the performances of some of the new generation image and video quality assessment metrics.

关键词： human visual system traditional image&video quality metrics the state-of-the-art image and video quality metrics

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Accurate Recognition of Kiwifruit Based on Improved YOLOv5 5

Accurate Recognition of Kiwifruit Based on Improved YOLOv5

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5th International conference on Natural Language processing, ICNLP 2023

作者： Wei, Sun Jun, Sun Yi Chen, Li Zhao Jing, Guo Xi'an University of Posts and Telecommunications School of Communications and Information Engineering Xi'an710121 China

ISBN: (纸本)9798350302219

In order to meet the urgent needs of automation and intelligent picking of kiwifruit, aiming at the problems of unreasonable construction of kiwifruit data set, low fruit recognition accuracy and poor spatial positioning in the natural environment of orchard, a precise recognition and visual positioning method of kiwifruit based on improved Yolov5s was proposed. In view of the growth characteristics of kiwifruit in trellis orchards, a multi-type kiwifruit data set was first constructed. Furthermore, the attention mechanism and multi-scale module are combined to improve the Yolov5s network structure, identify kiwifruit and extract the center coordinates of the prediction box. The experimental results show that the average accuracy of the model for six kiwifruit types under different weather and light conditions is 98 %. The single image recognition time of 1280× 720 pixel is about 13.8 ms, and the weight is only 15.21 Mb. It can be seen that this study can provide technical support for the vision system of kiwifruit automatic picking robot, and provide reference for the intelligent recognition and positioning of other fruits (such as apples, mangoes and oranges). © 2023 IEEE.

关键词： Orchards

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