Water Level Detection for Functionally Layered Video Coding

Iwahashi, Masahiro; Udomsiri, Sakol; Imai, Yoshiki; Muramatsu, Shogo

doi:10.1109/icip.2007.4379157

Cited by 9 publications

(6 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To interpret the field performance, however, the sources of uncertainty inherent with this novel technique must be described. Several studies propose imagebased water level measurement techniques (Chakravarthy et al, 2002;Iwahashi et al, 2007;Shin et al, 2008;Yu and Hahn, 2010) but none describe in detail the sources of uncertainty associated with using images as raw data. This article aims at filling this gap.…”

Section: Introductionmentioning

confidence: 99%

Source and magnitude of error in an inexpensive image-based water level measurement system

Gilmore

Bírgand

Chapman³

2013

Journal of Hydrology

View full text Add to dashboard Cite

Recent technological advances have opened the possibility to use webcams and images as part of the environmental monitoring arsenal. The potential sources and magnitude of uncertainties inherent to an image-based water level measurement system are evaluated in an experimental design in the laboratory. Sources of error investigated include image resolution, lighting effects, perspective, lens distortion and water meniscus. Image resolution and meniscus were found to weigh the most in the overall uncertainty of this system. Image distortion, although largely taken into account by the software developed, may also significantly add to uncertainty. Results suggest that ''flat'' images with little distortion are preferable. After correction for the water meniscus, images captured with a camera (12 mm or 16 mm focal lengths) positioned 4-7 m from the water level edge have the potential to yield water level measurements within ±3 mm when using this technique.

show abstract

Section: Introductionmentioning

confidence: 99%

Source and magnitude of error in an inexpensive image-based water level measurement system

Gilmore

Bírgand

Chapman³

2013

Journal of Hydrology

View full text Add to dashboard Cite

show abstract

“…The motion vector mv is estimated by (9) where pixel values of two frames at location n=(n 1 ,n 2 ) are denoted by x 1 (n) and x 2 (n). Denoting the forward transform and the backward transform of the discrete Fourier transform by F [ ] and F -1 [ ] respectively, the cost function E i in eq.…”

Section: Motion Estimationmentioning

confidence: 99%

“…When θ=45. 9 [dB] is required by a person for browsing, all the frequency bands and the bit planes must be transmitted. On the other hand, when σ=0 is required for the motion estimation, the minimum components are f r ×b p =1LL×1 and θ=4.64 [dB].…”

Section: Motion Estimation Errormentioning

confidence: 99%

See 1 more Smart Citation

Functionally layered coding for robot vision network

Iwahashi

Taguchi

Kimura

2009

2009 Picture Coding Symposium

Self Cite

View full text Add to dashboard Cite

This paper proposes a functionally layered video coding for robot vision network. Video signals from mobile robots are regularly transmitted to a remote robot. It uses the video to estimate locations of each of the mobile robots. As the need arises, a person browses the video to check the scenery. In such occasion, the functionally layered video coding regularly transmits the minimum components necessary for the motion estimation by the remote robot. For scenery browsing, only additional components are transmitted on demand. As a result, data volume to be transmitted is reduced in total. The proposed method decomposes the video into frequency bands and bit planes by means of the JPEG 2000. This report investigates the minimum components for the motion estimation in the robot to robot communication. It is confirmed that the proposed method can reduce total data volume of the robot vision network.

show abstract

“…As a drawback, image-based systems can be affected by lighting changes, camera movement and condensation on the lens [14,15]. The spreading use of unmanned aerial vehicles (UAVs) has paved the way for the integration of drone technology and optical sensing aimed at quantitatively estimating hydraulic data such as inundated areas (e.g., [16]), surface flow measurements (e.g., [17]), and water level estimations (e.g., [12]).…”

Section: Introductionmentioning

confidence: 99%

Water Level Measurements from Drones: A Pilot Case Study at a Dam Site

Ridolfi

Manciola

2018

Water

View full text Add to dashboard Cite

Unmanned Aerial Vehicles (UAVs) are now filling in the gaps between spaceborne and ground-based observations and enhancing the spatial resolution and temporal coverage of data acquisition. In the realm of hydrological observations, UAVs play a key role in quantitatively characterizing the surface flow, allowing for remotely accessing the water body of interest. In this paper, we propose a technology that uses a sensing platform encompassing a drone and a camera to determine the water level. The images acquired by means of the sensing platform are then analyzed using the Canny method to detect the edges of water level and of Ground Control Points (GCPs) used as reference points. The water level is then retrieved from images and compared to a benchmark value obtained by a traditional device. The method is tested at four locations in an artificial lake in central Italy. Results are encouraging, as the overall mean error between estimated and true water level values is around 0.05 m. This technology is well suited to improve hydraulic modeling and thus provides reliable support to flood mitigation strategies.

show abstract

Water Level Detection for Functionally Layered Video Coding

Cited by 9 publications

References 3 publications

Source and magnitude of error in an inexpensive image-based water level measurement system

Source and magnitude of error in an inexpensive image-based water level measurement system

Functionally layered coding for robot vision network

Water Level Measurements from Drones: A Pilot Case Study at a Dam Site

Contact Info

Product

Resources

About