Chunyuan Li^1,2,3, Peng Zhang^1,2,3, Shuangming Wang⁴, Lie Liu⁴, Mingquan Shi^2,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1197-1214, 2024, DOI:10.32604/cmc.2024.055893 - 15 October 2024

Abstract With the remarkable advancements in machine vision research and its ever-expanding applications, scholars have increasingly focused on harnessing various vision methodologies within the industrial realm. Specifically, detecting vehicle floor welding points poses unique challenges, including high operational costs and limited portability in practical settings. To address these challenges, this paper innovatively integrates template matching and the Faster RCNN algorithm, presenting an industrial fusion cascaded solder joint detection algorithm that seamlessly blends template matching with deep learning techniques. This algorithm meticulously weights and fuses the optimized features of both methodologies, enhancing the overall detection capabilities. Furthermore,… More >

Asifa Mehmood Qureshi¹, Naif Al Mudawi², Mohammed Alonazi³, Samia Allaoua Chelloug⁴, Jeongmin Park^5,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3683-3701, 2024, DOI:10.32604/cmc.2024.043611 - 26 March 2024

Abstract Road traffic monitoring is an imperative topic widely discussed among researchers. Systems used to monitor traffic frequently rely on cameras mounted on bridges or roadsides. However, aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger area. To this end, different models have shown the ability to recognize and track vehicles. However, these methods are not mature enough to produce accurate results in complex road scenes. Therefore, this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with… More >

R. Ganesan^1,*, G. Sankaranarayanan¹, M. Pradeep Kumar², V. K. Bupesh Raja¹

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 667-681, 2023, DOI:10.32604/iasc.2023.031932 - 29 September 2022

Abstract This research introduces a challenge in integrating and cleaning the data, which is a crucial task in object matching. While the object is detected and then measured, the vibration at different light intensities may influence the durability and reliability of mechanical systems or structures and cause problems such as damage, abnormal stopping, and disaster. Recent research failed to improve the accuracy rate and the computation time in tracking an object and in the vibration measurement. To solve all these problems, this proposed research simplifies the scaling factor determination by assigning a known real-world dimension to… More >

Sandeep Kaur^*, Bharat Bhushan Sagar

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1541-1559, 2023, DOI:10.32604/cmc.2023.032857 - 22 September 2022

Abstract Analysis and recognition of ancient scripts is a challenging task as these scripts are inscribed on pillars, stones, or leaves. Optical recognition systems can help in preserving, sharing, and accelerate the study of the ancient scripts, but lack of standard dataset for such scripts is a major constraint. Although many scholars and researchers have captured and uploaded inscription images on various websites, manual searching, downloading and extraction of these images is tedious and error prone. Web search queries return a vast number of irrelevant results, and manually extracting images for a specific script is not More >

Muhammad Hameed Siddiqi^1,*, Helal Alshammari¹, Amjad Ali², Madallah Alruwaili¹, Yousef Alhwaiti¹, Saad Alanazi¹, M. M. Kamruzzaman¹

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 611-634, 2022, DOI:10.32604/cmc.2022.024760 - 24 February 2022

Abstract Human activity recognition (HAR) can play a vital role in the monitoring of human activities, particularly for healthcare conscious individuals. The accuracy of HAR systems is completely reliant on the extraction of prominent features. Existing methods find it very challenging to extract optimal features due to the dynamic nature of activities, thereby reducing recognition performance. In this paper, we propose a robust feature extraction method for HAR systems based on template matching. Essentially, in this method, we want to associate a template of an activity frame or sub-frame comprising the corresponding silhouette. In this regard,… More >

Yong Ding¹, Lei Tian¹, Bo Han², Huiyong Wang^2,*, Yujue Wang¹, James Xi Zheng³

CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 727-738, 2019, DOI:10.32604/cmc.2019.06220

Abstract Currently, many biometric systems maintain the user’s biometrics and templates in plaintext format, which brings great privacy risk to uses’ biometric information. Biometrics are unique and almost unchangeable, which means it is a great concern for users on whether their biometric information would be leaked. To address this issue, this paper proposes a confidential comparison algorithm for iris feature vectors with masks, and develops a privacy-preserving iris verification scheme based on the El Gamal encryption scheme. In our scheme, the multiplicative homomorphism of encrypted features is used to compare of iris features and their mask More >

W.C. Wang¹, F.L. Chang², Y.L. Liu¹, X. J. Wu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.107, No.5, pp. 411-431, 2015, DOI:10.3970/cmes.2015.107.411

Abstract The detection of macroscopic irregularities is an essential procedure during the production of gears, and it helps to guarantee the quality of electromechanical transmission equipment. The working principles of template matching and the image nonequivalence operation are described in detail in this paper. Gray-level transformation, edge-preserving filtering, image segmentation, feature extraction, and pattern recognition were analyzed, leading to the design of a defect detection system based on template matching and the nonequivalence operation, followed by the development of a hardware platform and application software for the system. The experimental results indicate that the proposed detection More >