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STUDY ON MEASUREMENT OF WOOD SURFACEROUGHNESS BY computer vision

Journal of Northeast Forestry University 1992年第1期3卷 75-81页

作者： Zhao XuezengNortheast Forestry University Northeast Forestry University China

The working processes, machining devices and tools, cutting amount, consumption of materials, productivity and quality of products are directly affected by wood surface roughness. This paper gives an extensive review of methods used previously to measure wood surface roughness, and concludes that computer vision.is the most suitable technique. The preliminary study shows that computer vision.method has the advantages of a noncontact, three-dimensional measurement, high speed and well correlates with stylus tracing method. This method can be used in classification and in-time measurement of wood surface roughness after being improved.

关键词： Wood Surface roughness measurement computer vision.

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Segment Anything Is Not Always Perfect: An Investigation of SAM on Different Real-world Applications

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Machine Intelligence Research 2024年第4期21卷 617-630页

作者： Wei Ji Jingjing Li Qi Bi Tingwei Liu Wenbo Li Li Cheng University of Alberta Edmonton T6G 2R3Canada Wuhan University Wuhan 430072China Dalian University of Technology Dalian 116024China Samsung Research America Mountain View 94043USA

Recently,Meta AI Research approaches a general,promptable segment anything model(SAM)pre-trained on an unprecedentedly large segmentation dataset(SA-1B).Without a doubt,the emergence of SAM will yield significant benefits for a wide array of practical image segmentation *** this study,we conduct a series of intriguing investigations into the performance of SAM across various applications,particularly in the fields of natural images,agriculture,manufacturing,remote sensing and *** analyze and discuss the benefits and limitations of SAM,while also presenting an outlook on its future development in segmentation *** doing so,we aim to give a comprehensive understanding of SAM's practical *** work is expected to provide insights that facilitate future research activities toward generic *** code is publicly available at https://***/LiuTingWed/SAM-Not-Perfect.

关键词： Segment anything model(SAM) visual perception segmentation foundational model computer vision.

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Multifunctional Optical Image Processor

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光电工程 1992年第5期 22-30页

作者： David Casasent Carnegie Mellon University Center for Excellence in Optical Data Processing Department of Electrical and computer Engineering Pittsburgh. PA 15213. USA

A multifunctional optical imagc processor capable of morphological,feature extraction and correlation operations for low,medium and high-level computervision.is described,A morphological processor achieves detection and image enhance-ment. A correlator achieves recognition(and can also achieve detection and identi-fication). A feature extractor is useful for identification in large class problemsin scene analys *** optical processors can be realized on the same programmableoptical processor.

关键词： Optical processors Image processors Optical correlators Target recognition computer vision.

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Machine vision

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2004年

作者： Wesley E. Snyder Hairong Qi

ISBN: (纸本)9780521830461

Providing all the necessary theoretical tools, this comprehensive introduction to machine vision.shows how these tools are applied in actual image processing and machine vision.systems. A key feature is the inclusion of many programming exercises giving insights into the development of practical image processing algorithms. A CD-ROM containing software and data used in these exercises is also included. Aimed at graduate students in electrical engineering, computer science, and mathematics, the book will be a useful reference for professionals as well.

关键词： computer vision.

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Computational vision.in Neural and Machine Systems

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2007年

作者： Laurence R. Harris Michael R. M. Jenkin

ISBN: (纸本)9780521862608

Computational vision.deals with the underlying mathematical and computational models for how visual information is processed. Whether the processing is biological or machine, there are fundamental questions related to how the information is processed. How should information be represented? How should information be transduced in order to highlight features of interest while suppressing noise and other artefacts of the image capture process? Computational vision.in Neural and Machine Systems address these and other questions in 13 chapters, divided into three sections, which overlap between biological and computational systems: dynamical systems; attention, motion, and eye-movements; and stereovision. The editors have brought together the best and brightest minds in the field of computational vision. combining research from both biology and computing and enhancing the developing synergy between computational and biological visual modelling communities. Aimed at researchers and graduate students in computational or biological vision. neuroscience, and psychology.

关键词： computer vision.

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STUDY ON THREE-DIMENSIONAL SURFACE RECONSTRUCTION OF BLACK MELON SEEDS USING PHOTOMETRIC STEREO

STUDY ON THREE-DIMENSIONAL SURFACE RECONSTRUCTION OF BLACK M...

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2006年中国机械工程学会年会暨中国工程院机械与运载工程学部首届年会

作者： CHEN Ying, LI Haoyu, LI Wei College of Engineering, China Agricultural University, Beijing 100083, China

In this paper, the 3-D surface reconstruction method of black melon seeds based on photometric stereo was studied, which was then used to identify the wrinkled seeds. After the image capturing system

关键词： Photometric stereo 3-D surface reconstruction black melon seeds computer vision.

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STUDY ON THREE-DIMENSIONAL SURFACE RECONSTRUCTION OF BLACK MELON SEEDS USING PHOTOMETRIC STEREO

STUDY ON THREE-DIMENSIONAL SURFACE RECONSTRUCTION OF BLACK M...

引用

International Technology and Innovation Conference 2006

作者： CHEN Ying LI Haoyu LI Wei College of Engineering China Agricultural University Beijing 100083 China

＜正＞In this paper, the 3-D surface reconstruction method of black melon seeds based on photometric stereo was studied, which was then used to identify the wrinkled seeds. After the image capturing system being set up, the system accuracy was calibrated by reconstructing a standard hemispherical object. Then, the whole 3-D surface of a seed was built by reconstructing its central and periphery region with PS separately for the two regions are of great colour differences. Finally, experiments were done to show that cross surface area of the reconstructed surface can be used as wrinkle identification parameter with the identification threshold of 9. Under this threshold more than 90% of wrinkled seeds could be successfully identified while only 5% of normal seeds being identified as wrinkled.

关键词： Photometric stereo 3-D surface reconstruction black melon seeds computer vision.

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Machine vision

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丛书名：经典原版书库

2005年

作者： Snyder Wesley E.

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Machine vision

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2004年

作者： Wesley E. Snyder Hairong Qi.

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