Min-local-LoG filter for detecting small targets in cluttered background

2011 ◽  
Vol 47 (2) ◽  
pp. 105 ◽  
Author(s):  
S. Kim
Keyword(s):  
Cluttered Background ◽  
Small Targets

Use of hybrid shots in planning Perfexion Gamma Knife treatments for lesions close to critical structures

2008 ◽  
Vol 109 (Supplement) ◽  
pp. 34-40 ◽  
Author(s):  
Paula L. Petti ◽  
David A. Larson ◽  
Sandeep Kunwar
Keyword(s):  
Optic Nerve ◽  
Gamma Knife ◽  
Pituitary Tumor ◽  
Metastatic Lesion ◽  
Conformity Index ◽  
Target Coverage ◽  
Critical Areas ◽  
Planning Technique ◽  
Small Targets ◽  
Critical Structure

Object The authors investigated the use of different collimator values in different sectors (hybrid shots) when treating patients with lesions close to critical structures with the Perfexion model Gamma Knife. Methods Twelve patients with various tumors (6 with a pituitary tumor, 3 with vestibular schwannoma, 2 with meningioma, and 1 with metastatic lesion) that were within 4 mm of the brainstem, optic nerve, pituitary stalk, or cochlea were considered. All patients were treated at the authors' institution between June 2007 and March 2008. The patients' treatments were replanned in 2 different ways. In the first plan, hybrid shots were used such that the steepest dose gradient was aligned with the junction between the target and the critical structure(s). This was accomplished by placing low-value collimators in appropriate sectors. In the second plan, no hybrid shots were used. Sector blocking (either manual or dynamic) was required for all plans to reduce the critical structure doses to acceptable levels. Prescribed doses ranged from 12 to 30 Gy at the periphery of the target. The plans in each pair were designed to be equally conformal in terms of both target coverage (as measured by the Paddick conformity index) and critical structure sparing. Results The average number of shots required was roughly the same using either planning technique (16.7 vs 16.6 shots with and without hybrids). However, for all patients, the number of blocked sectors required to protect critical areas was larger when hybrid shots were not used. On average, nearly twice as many blocked sectors (14.8 vs 7.0) were required for the plans that did not use hybrid shots. The number of high-value collimators used in each plan was also evaluated. For small targets (≤ 1 cm3), for which 8 mm was considered a high value for the collimator, plans employing hybrids used an average of 2.3 times as many 8-mm sectors as did their nonhybrid counterparts (7.4 vs 3.2 sectors). For large targets (> 1 cm3), for which 16 mm was considered a high value for the collimator, hybrid plans used an average of 1.4 times as many 16-mm sectors as did the plans without hybrids (10.7 vs 7.7 sectors). Decreasing the number of blocked sectors and increasing the number of high-value collimator sectors led to use of shorter beam-on times. Beam-on times were 1–39% higher (average 17%) when hybrid shots were not allowed. The average beam-on time for plans with and without hybrid shots was 67.4 versus 78.4 minutes. Conclusions The judicious use of hybrid shots in patients for whom the target is close to a critical structure is an efficient way to achieve conformal treatments while minimizing the beam-on time. The reduction in beam-on time with hybrid shots is attributed to a reduced use of blocked sectors and an increased number of high-value collimator sectors.

Mechanism for Visual Detection of Small Targets in Insects

2013 ◽  
Author(s):  
David C. O'Carroll ◽  
Steven D. Wiederman ◽  
Patrick A. Shoemaker
Keyword(s):  
Visual Detection ◽  
Small Targets

scholarly journals Robust Principal Component Analysis-Based Infrared Small Target Detection

2019 ◽  
Vol 33 ◽  
pp. 9925-9926
Author(s):  
Qiwei Chen ◽  
Cheng Wu ◽  
Yiming Wang
Keyword(s):  
Iteration Process ◽  
Principal Component ◽  
Component Analysis ◽  
Low Rank ◽  
Small Target ◽  
Frame Sequence ◽  
Augmented Lagrange Multiplier ◽  
Small Targets ◽  
Infrared Small Target ◽  
Augmented Lagrange Multiplier Method

A method based on Robust Principle Component Analysis (RPCA) technique is proposed to detect small targets in infrared images. Using the low rank characteristic of background and the sparse characteristic of target, the observed image is regarded as the sum of a low-rank background matrix and a sparse outlier matrix, and then the decomposition is solved by the RPCA. The infrared small target is extracted from the single-frame image or multi-frame sequence. In order to get more efficient algorithm, the iteration process in the augmented Lagrange multiplier method is improved. The simulation results show that the method can detect out the small target precisely and efficiently.

scholarly journals Generalist camouflage can be more successful than microhabitat specialisation in natural environments

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Emmanuelle Sophie Briolat ◽  
Lina María Arenas ◽  
Anna E. Hughes ◽  
Eric Liggins ◽  
Martin Stevens
Keyword(s):  
Survival Benefit ◽  
Search Task ◽  
Natural Scenes ◽  
Science Methods ◽  
Natural Environments ◽  
Background Matching ◽  
Computer Based ◽  
Visual Scenes ◽  
Small Targets ◽  
Predator Defence

Abstract Background Crypsis by background-matching is a critical form of anti-predator defence for animals exposed to visual predators, but achieving effective camouflage in patchy and variable natural environments is not straightforward. To cope with heterogeneous backgrounds, animals could either specialise on particular microhabitat patches, appearing cryptic in some areas but mismatching others, or adopt a compromise strategy, providing partial matching across different patch types. Existing studies have tested the effectiveness of compromise strategies in only a limited set of circumstances, primarily with small targets varying in pattern, and usually in screen-based tasks. Here, we measured the detection risk associated with different background-matching strategies for relatively large targets, with human observers searching for them in natural scenes, and focusing on colour. Model prey were designed to either ‘specialise’ on the colour of common microhabitat patches, or ‘generalise’ by matching the average colour of the whole visual scenes. Results In both the field and an equivalent online computer-based search task, targets adopting the generalist strategy were more successful in evading detection than those matching microhabitat patches. This advantage occurred because, across all possible locations in these experiments, targets were typically viewed against a patchwork of different microhabitat areas; the putatively generalist targets were thus more similar on average to their various immediate surroundings than were the specialists. Conclusions Demonstrating close agreement between the results of field and online search experiments provides useful validation of online citizen science methods commonly used to test principles of camouflage, at least for human observers. In finding a survival benefit to matching the average colour of the visual scenes in our chosen environment, our results highlight the importance of relative scales in determining optimal camouflage strategies, and suggest how compromise coloration can succeed in nature.

scholarly journals Design of bio-inspired binocular UAV detection system based on improved STC algorithm of scale transformation and occlusion detection

2021 ◽  
Vol 13 ◽  
pp. 175682932110048
Author(s):  
Huajun Song ◽  
Yanqi Wu ◽  
Guangbing Zhou
Keyword(s):  
Detection System ◽  
Rapid Development ◽  
Reference Value ◽  
Scale Transformation ◽  
Hardware System ◽  
Time Requirements ◽  
Aerial Vehicle ◽  
Spatio Temporal ◽  
Small Targets ◽  
Vision Detection

With the rapid development of drones, many problems have arisen, such as invasion of privacy and endangering security. Inspired by biology, in order to achieve effective detection and robust tracking of small targets such as unmanned aerial vehicles, a binocular vision detection system is designed. The system is composed of long focus and wide-angle dual cameras, servo pan tilt, and dual processors for detecting and identifying targets. In view of the shortcomings of spatio-temporal context target tracking algorithm that cannot adapt to scale transformation and easy to track failure in complex scenes, the scale filter and loss criterion are introduced to make an improvement. Qualitative and quantitative experiments show that the designed system can adapt to the scale changes and partial occlusion conditions in the detection, and meets the real-time requirements. The hardware system and algorithm both have reference value for the application of anti-unmanned aerial vehicle systems.

scholarly journals Small Floating Target Detection Method Based on Chaotic Long Short-Term Memory Network

2021 ◽  
Vol 9 (6) ◽  
pp. 651
Author(s):  
Yan Yan ◽  
Hongyan Xing
Keyword(s):  
High Frequency ◽  
Short Term Memory ◽  
Detection Method ◽  
Low Frequency ◽  
Sea Clutter ◽  
Short Term ◽  
Term Memory ◽  
Memory Network ◽  
Long Short Term Memory ◽  
Small Targets

In order for the detection ability of floating small targets in sea clutter to be improved, on the basis of the complete ensemble empirical mode decomposition (CEEMD) algorithm, the high-frequency parts and low-frequency parts are determined by the energy proportion of the intrinsic mode function (IMF); the high-frequency part is denoised by wavelet packet transform (WPT), whereas the denoised high-frequency IMFs and low-frequency IMFs reconstruct the pure sea clutter signal together. According to the chaotic characteristics of sea clutter, we proposed an adaptive training timesteps strategy. The training timesteps of network were determined by the width of embedded window, and the chaotic long short-term memory network detection was designed. The sea clutter signals after denoising were predicted by chaotic long short-term memory (LSTM) network, and small target signals were detected from the prediction errors. The experimental results showed that the CEEMD-WPT algorithm was consistent with the target distribution characteristics of sea clutter, and the denoising performance was improved by 33.6% on average. The proposed chaotic long- and short-term memory network, which determines the training step length according to the width of embedded window, is a new detection method that can accurately detect small targets submerged in the background of sea clutter.

Night-time disability glare of constant-light LED traffic monitoring fill light

2021 ◽  
pp. 147715352098226
Author(s):  
X Cai ◽  
L Quan ◽  
J Wu ◽  
Y He
Keyword(s):  
Dynamic Range ◽  
Road Traffic ◽  
Reaction Times ◽  
High Dynamic Range ◽  
Luminance Contrast ◽  
Traffic Monitoring ◽  
Constant Light ◽  
Night Time ◽  
Disability Glare ◽  
Small Targets

Fill light, used to helps cameras capture road traffic conditions at night, can lead to serious visual consequences for drivers. Research on disability glare from LED fill light is scarce and therefore this study explored strategies for controlling disability glare of constant-light LED traffic monitoring fill light. The threshold increment was used as an index to evaluate disability glare. The effective disability glare area of LED traffic monitoring fill light was determined based on high dynamic range technology. According to visual efficacy theory, there is a relationship between disability glare conditions and reaction times. The influencing factors include background luminance, luminance contrast and fill light luminance. The results showed that disability glare was the most intense in a range of 20 m to 30 m in front of LED fill light. To reduce the effect of disability glare on drivers, luminance contrast between small targets and the road surface should be greater than 0.5. The fill light luminance should not be greater than 100,000 cd/m2.

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