This paper presents a keypoint detection method based on the Laplacian of Gaussian (LoG). In contrast to the Difference of Gaussian (DoG)-based keypoint detection method used in Scale Invariant Feature Transform (SIFT), we focus on the LoG operator and its higher order derivatives. We provide mathematical analogies between higher order DoG (HDoG) and higher order LoG (HLoG) and experimental results to show the effectiveness of the proposed HLoG-based keypoint detection method. The performance of the HLoG is evaluated with four different tests: i) a repeatability test of the keypoints detected across images under various transformations, ii) image retrieval, iii) panorama stitching and iv) 3D reconstruction. The proposed HLoG method provides comparable performance to HDoG and the combination of HLoG and HDoG provides significant improvements in various keypoint-related computer vision problems.

The moving picture experts group (MPEG) immersive video (MIV) technology has been actively developed and standardized to efficiently deliver immersive video to viewers in order for them to experience immersion and realism in various realistic and virtual environments. Such services are provided by MIV technology, which uses multiview videos as input. The pruning process, which is an important component of MIV technology, reduces interview redundancy in multiviews videos. The primary aim of the pruning process is to reduce the amount of data that available video codec must handle. In this study, two approaches are presented to improve the existing pruning algorithm. The first method determines the order in which images are pruned. The amount of overlapping region between the source views is then used to determine the pruning order. The second method considers global region‐wise color similarity to minimize matching ambiguity when determining the pruning area. The proposed methods are evaluated under common test condition of MIV, and the results show that incorporating the proposed methods can improve both objective and subjective quality.

Virtual source location information (VSLI) has been newly utilized as a spatial cue for compact representation of multichannel audio. This information is represented as the azimuth of the virtual source vector. The superiority of VSLI is confirmed by comparison of the spectral distances, average bit rates, and subjective assessment with a conventional cue.

Hybrid cryptographic protocol was proposed by integrating quantum-safe algorithms (Kyber and Dilithium) together with a classical ECDSA-based signature scheme to verify secure proof on blockchain. Since quantum computers pose some loopholes in existing cryptography algorithms, the proposed mechanism addresses those vulnerabilities by maintaining compatibility with the existing infrastructure. The protocol integrates post-quantum key exchange to derive shared secrets securely. The shared secrets are used to enable hybrid encryption for efficient data protection. Additionally, the implementation uses a dual-signature approach, using quantum safe and classical signatures. These signatures are combined to ensure robust and tamper-resistant proof verification. The deployed solution validates its feasibility and efficiency for smart contract-based verification. The protocol maintains backward compatibility with existing systems while providing strong resistance to quantum attacks. Benchmark results demonstrate the system’s scalability and robustness under high transaction loads, with efficient gas usage for on-chain proof validation. This approach paves the way for post-quantum secure applications, including verifiable proofs, secure key exchanges, and decentralized systems resilient to quantum adversaries.