Pill Recognition Using Imprint Information by Two-Step Sampling Distance Sets

2014 ◽  
Author(s):  
Jiye Yu ◽  
Zhiyuan Chen ◽  
Sei-ichiro Kamata
Keyword(s):  
Sampling Distance ◽  
Distance Sets

Development of a Non-Contact Tool Setting System for Precision Diamond Turning

2006 ◽  
Vol 505-507 ◽  
pp. 367-372 ◽  
Author(s):  
Choung Lii Chao ◽  
T.A. Cheng ◽  
D.C. Lou ◽  
Chung Woei Chao
Keyword(s):  
Contact Point ◽  
Diamond Turning ◽  
Optical Diffraction ◽  
Sampling Step ◽  
Error Band ◽  
Sampling Distance ◽  
Tool Shape ◽  
Tool Setting ◽  
Ultra Precision ◽  
Cnc Controller

Precise and efficient tool setting technique and accurate tool shape monitoring are of essential importance in ultra-precision diamond turning operation. The traditional way of tool setting are typically laborious, inefficient and rely heavily on experience. A big part of the tool setting is done by using a contact probe such as LVDT. The contact tool setting station can normally, depending on the resolution of the probes, place the tool tip to within a 1~10μm positioning accuracy. However, it is running the risk of damage the delicate tool tip and has the ambiguity introduced by contact point of tool and touch probe. The optical/non-contact way of setting the tool do have the advantage of not having to touch the tool, but its resolution is limited by the optical diffraction limit and the resolution of the CCD device used (mm/pixel). A non-contact precision tool setting system is developed and built in this study using edge-detection image processing and sub-pixel dividing techniques in conjunction with CNC controller of the precision turning machine to improve the system presently available. Depending on the sampling distance of the images, the error band gets wider when the sampling step becomes larger. In the case of 0.1μm sampling distance the obtained error band was within ±0.1μm and the results showed that tools of different shapes namely round, half-round and sharp tool could all be positioned to within an error band of ±0.1μm by using the developed tool setting system.

Resolving pre-collapse slope motion at the February 2021 Chamoli rock-ice avalanche via feature tracking of optical satellite imagery

2021 ◽  
Author(s):  
Maximillian Van Wyk de Vries ◽  
Shashank Bhushan ◽  
David Shean ◽  
Etienne Berthier ◽  
César Deschamps-Berger ◽  
...  
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Feature Tracking ◽  
Satellite Image ◽  
Image Feature ◽  
Sampling Distance ◽  
Velocity Changes ◽  
The Stability ◽  
Slide Area ◽  
Ice Avalanche

<p>On the 7<sup>th</sup> of February 2021, a large rock-ice avalanche triggered a debris flow in Chamoli district, Uttarakhand, India, resulting in over 200 dead or missing and widespread infrastructure damage. The rock-ice avalanche originated from a steep, glacierized north-facing slope with a history of instability, most recently a 2016 ice avalanche. In this work, we assess whether the slope exhibited any precursory displacement prior to collapse. We evaluate monthly slope motion over the 2015 and 2021 period through feature tracking of high-resolution optical satellite imagery from Sentinel-2 (10 m Ground Sampling Distance) and PlanetScope (3-4 m Ground Sampling Distance). Assessing slope displacement of the underlying rock is complicated by the presence of glaciers over a portion of the collapse area, which display surface displacements due to internal ice deformation. We overcome this through tracking the motion over ice-free portions of the slide area, and evaluating the spatial pattern of velocity changes in glaciated areas. Preliminary results show that the rock-ice avalanche bloc slipped over 10 m in the 5 years prior to collapse, with particularly rapid slip occurring in the summer of 2017 and 2018. These results provide insight into the precursory conditions of the deadly rock-ice avalanche, and highlight the potential of high-resolution optical satellite image feature tracking for monitoring the stability of high-risk slopes.</p>

On the Hausdorff dimensions of distance sets

Mathematika ◽  
1985 ◽  
Vol 32 (2) ◽  
pp. 206-212 ◽  
Author(s):  
K. J. Falconer
Keyword(s):  
Hausdorff Dimensions ◽  
Distance Sets

Hausdorff dimension and distance sets

1994 ◽  
Vol 87 (1-3) ◽  
pp. 193-201 ◽  
Author(s):  
Jean Bourgain
Keyword(s):  
Hausdorff Dimension ◽  
Distance Sets

scholarly journals PEMETAAN PERKEBUNAN SAWIT RAKYAT DARI FOTO UDARA NON METRIK MENGGUNAKAN ANALISIS BERBASIS OBJEK

2019 ◽  
Vol 21 (1) ◽  
pp. 53 ◽  
Author(s):  
Agung Syetiawan ◽  
Muhammad Haidar
Keyword(s):  
Image Analysis ◽  
Oil Palm ◽  
Aerial Photo ◽  
Aerial Photos ◽  
Accuracy Requirement ◽  
Object Based Image Analysis ◽  
Oil Palm Plantation ◽  
East Kalimantan ◽  
Sampling Distance ◽  
Object Based

<p align="center"><strong>ABSTRAK</strong></p><p>Beberapa tahapan penerbitan Surat Tanda Daftar Usaha Perkebunan untuk Budidaya <br /> (STD-B) yang digunakan dalam kegiatan perkebunan sawit dengan luas kurang dari 25 ha yaitu pemeriksaan lapangan dan pemetaan yang dilakukan oleh tim verifikasi lintas sektoral. Penerbitan STD-B harus melampirkan peta sebagai persyaratan dalam pendaftaran STD-B, yaitu peta yang memiliki skala 1:2.000. Untuk itu diperlukan teknologi pemetaan yang mumpuni guna memenuhi kebutuhan pemetaan tersebut. Seiring dengan kemajuan teknologi, pemetaan udara menggunakan kamera non-metrik menghasilkan tampilan permukaan bumi secara detil. Tujuan penelitian adalah mengkaji kemampuan pemetaan udara menggunakan kamera non-metrik untuk pembuatan peta sawit rakyat. Proses akuisisi pemetaan sawit rakyat dilakukan di daerah Labanan Makmur Kalimantan Timur. Proses pemetaan udara menggunakan wahana tanpa awak (WTA) <em>fixed wing</em> dengan ketinggian terbang 420 meter diatas permukaan tanah menghasilkan 186 foto dengan <em>sidelap</em> dan <em>overlap</em> foto sebesar 70% dan 80%. Proses identifikasi tanaman kelapa sawit rakyat menggunakan pendekatan <em>Object Based Image Analysis</em> (OBIA). Output akhir yaitu menghasilkan foto udara dengan nilai GSD (<em>Ground Sampling Distance</em>) sebesar 13 cm/pix. Proses pengolahan foto udara dilakukan dengan memasukkan GCP dan tanpa menggunakan GCP. Hasil evaluasi geometrik nilai akurasi horisontal dengan menggunakan GCP diperoleh akurasi sebesar 0,250 meter sementara tanpa menggunakan GCP diperoleh akurasi sebesar 4,222 meter. Dari hasil evaluasi geometrik tersebut maka foto udara dengan menggunakan GCP memenuhi ketelitian geometri untuk pembuatan peta pada skala 1: 1.000, sementara foto udara tanpa menggunakan GCP memenuhi pada skala 1: 25.000. Proses pemetaan foto udara menggunakan kamera non-metrik ditambahkan dengan pengukuran GCP bisa digunakan sebagai acuan yang digunakan untuk membuat peta lampiran pendaftaran STD-B.</p><p> </p><p align="center"><strong><em>ABSTRACT</em></strong></p><p><em>Several phases in the issuance of register for plantation cultivation used for smallholder oil palm plantation with an area of less than 25 ha are field inspection and mapping that conducted by a cross-sectoral verification team. Issuance of register for plantation cultivation must attach the map as required in scale of 1:2.000. Thus, it requires robust mapping technology to meet certain standards. Along with advances in technology, aerial photo using non-metric cameras produces detailed view of the earth's surface. The aim of the study is to examine the ability of aerial photo using non-metric cameras to map smallholder oil palm plantation. The acquisition of smallholder oil palm plantation mapping is carried out in the Labanan Makmur Village, East Kalimantan. Aerial photos acquisition used a fixed-wing UAV with a flight altitude of 420 meters above ground and produced 186 photos with sidelap and overlap of 70% and 80% respectively. </em><em>The process of identifying </em><em>smallholder oil palm plantation</em><em> used the Object Based Image Analysis (OBIA) approach. </em><em>The final output is to produce aerial photos with a value of Ground Sampling Distance (GSD) of 13 cm/pixel. Aerial photo processing is performed either by using GCPs and without GCPs. </em><em>The results of geometric evaluation of horizontal accuracy value using GCP is 0.250 meters while without using GCP is 4.222 meters. </em><em>The results of the geometric evaluation showed that aerial photo using GCP meet the accuracy requirement for map in scale of 1:1,000; whilst aerial photo not using GCP could be utilized for mapping in scale of 1:25,000. Aerial photo using a non-metric camera combined with GCPs measurements can be used as a data source used to produces</em><em> the smallholder oil palm plantation map.</em></p>

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