The first complete description of SweepLSD is given, a line segment detector that reads the image exactly once and emits each segment within a few rows of its last pixel passing the scan line, with the tightest frame-time distribution and the best per-segment direction accuracy of the four detectors.
Abstract
We present SweepLSD, a line segment detector that reads the image exactly once and emits each segment within a few rows of its last pixel passing the scan line. Every stage, including connected-component labeling and the final line test, processes the image as a row stream: intermediate memory is O(width) rather than O(pixels), and the per-pixel core is integer-only. We give the first complete description of the algorithm, designed in the author's 2014 master's thesis but never published, together with an open-source C++17 implementation and an FPGA realization -- held bit-exact against the software in its hardware configuration -- detecting segments in live 1080p30 video on 2009-era silicon without frame buffer or external memory. On structure-rich public 4K photographs downscaled to Full-HD, one CPU thread detects segments in ~11 ms -- 4.6x/5.2x/25x faster than the original authors'implementations of ELSED, EDLines, and LSD -- with the tightest frame-time distribution and the best per-segment direction accuracy of the four detectors, and curve rejection by design, while trailing ELSED in F-score on synthetic ground truth. A Manhattan-frame vanishing-point study on York Urban and NYU-VP scores every detector under a selection/evaluation-separated best-estimator-per-detector protocol, under which SweepLSD leads on NYU-VP by ~0.3 degrees and trails by 0.1 degrees on York Urban, with the fastest end-to-end pipeline of the four detectors on both. A single-frame camera-attitude application, evaluated on synthetic scenes with exact ground truth and on EuRoC and TUM-VI, matches the baselines'accuracy at a fraction of their memory, and drives a 4K horizon lock to 0.06 degrees median attitude error at 32 ms median per frame.
Neuro-formal verification is introduced, which harnesses that automation for developers of mainstream programming languages and returns a Dafny proof of correctness or of a bug on 57% of the entries at 92% precision, and a CBMC counterexample for 63% of the buggy programs at 90% precision.
An audit-and-placebo protocol is proposed that separates verifier artifacts, interaction scaffolding, and grounded feedback credit in evaluations of self-evolving test generators in evaluations of self-evolving test generators.
Yunhao Liang, Chengguang Gan, Ruixuan Ying et al.· 0 citations
This study examined whether introductory Qiskit homework could remain autogradable while requiring students to run, review, and discuss results rather than banning AI.
This prototype MRG image translocation software was helpful to 69% of patients with binocular diplopia, but limited by large angle strabismus because of the limited instrument field of view.
Edsel B Ing, Kevin Sha, Sarosh Dandoti et al.· Journal of neuro-ophthalmolo...· 0 citations
A diagnostic support system based on a unified web platform that classifies patients according to the risks of developing three diseases based on regularly collected clinical or audio data using classical supervised learning algorithms is presented.
Vedamurthy D R, Dr. Anup Ritti, A. Bibi et al.· International Journal for Re...· 0 citations
A high initial investment in acquiring environmentally friendly products can discourage
institutions from adopting them. This study explored the extent to which eco-friendly products
contribute to supply chain resilience and operational performance at the Nigerian Maritime
University. The study employed a quantitative survey method administering a sample of 303copies
questionnaire to the staff of the organization using a stratified sampling technique. The hypotheses
were tested and analyzed using a regression method with the aid of Minitab software. The
regression analysis indicates eco-friendly products significantly relates to operational efficiency
in Nigerian Maritime University, South-South Nigeria. The model regression indicates (R² = 99.20,
B = 1.039, β = 0.0162, p = 0.000); indicating that the model is a good fit. The coefficient 1.0399
is highly significant (p < 0.001). This indicates a positive and strong effect, explaining that for
every one-unit increase in eco-friendly products, the operational efficiency increases by
approximately 1.039 units. The NOVA result confirms F = 4117.07, p < 0.001. The study
concludes that the adoption of eco-friendly products plays a significant and positive role in
enhancing organizational sustainability performance or resilience. Organizations should embed
eco-friendly product selection into their procurement guidelines to promote sustainable
operations. Management should invest in environmentally friendly technologies and capacity
building initiatives to support the transition to sustainable practices.
Ikenna Christopher Ugwu· IIARD International Journal...· 0 citations
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