An efficient interactive segmentation algorithm using color correction for underwater images

Sudhakara, M.; Meena, M. Janaki

doi:10.1007/s11276-019-02044-0

Cited by 6 publications

(5 citation statements)

References 12 publications

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“…There are several algorithms based on pixels, gradients, textures and many other descriptors for object detection in underwater vision systems ( Sudhakar and Meena, 2019 ). Some of the most used methods for circle detection are based on the Hough transform, which require a high computational cost, which translates in a slow performance for a system with limited computational capabilities, as is the case with most the AUVs.…”

Section: Methodsmentioning

confidence: 99%

“…In addition, as the color of the ball will be affected to depth (in the sea), the detector had to be also robust to saturation. Although we know that the target object has a specific geometry, we also know that edge-detection based methods, which use frequency information for compute gradient descriptors (like Canny and Sobel), will have a poor performance compared when they are used in a well lit enviroment ( Sudhakar and Meena, 2019 ). We decided to use the HSV color space similar to the work of Balazs Suto et al , which has proven to have robustness properties for color classification in addition to having a lower computational cost.…”

Section: Methodsmentioning

confidence: 99%

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A Mirror-Based Active Vision System for Underwater Robots: From the Design to Active Object Tracking Application

Noel

Torres-Méndez

2021

Front. Robot. AI

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A mirror-based active system capable of changing the view’s direction of a pre-existing fixed camera is presented. The aim of this research work is to extend the perceptual tracking capabilities of an underwater robot without altering its structure. The ability to control the view’s direction allows the robot to explore its entire surroundings without any actual displacement, which can be useful for more effective motion planning and for different navigation strategies, such as object tracking and/or obstacle evasion, which are of great importance for natural preservation in environments as complex and fragile as coral reefs. Active vision systems based on mirrors had been used mainly in terrestrial platforms to capture the motion of fast projectiles using high-speed cameras of considerable size and weight, but they had not been used on underwater platforms. In this sense, our approach incorporates a lightweight design adapted to an underwater robot using affordable and easy-access technology (i.e., 3D printing). Our active system consists of two arranged mirrors, one of which remains static in front of the robot’s camera, while the orientation of the second mirror is controlled by two servomotors. Object tracking is performed by using only the pixels contained on the homography of a defined area in the active mirror. HSV color space is used to reduce lighting change effects. Since color and geometry information of the tracking object are previously known, a window filter is applied over the H-channel for color blobs detection, then, noise is filtered and the object’s centroid is estimated. If the object is lost, a Kalman filter is applied to predict its position. Finally, with this information, an image PD controller computes the servomotor articular values. We have carried out experiments in real environments, testing our active vision system in an object-tracking application where an artificial object is manually displaced on the periphery of the robot and the mirror system is automatically reconfigured to keep such object focused by the camera, having satisfactory results in real time for detecting objects of low complexity and in poor lighting conditions.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

A Mirror-Based Active Vision System for Underwater Robots: From the Design to Active Object Tracking Application

Noel

Torres-Méndez

2021

Front. Robot. AI

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“…Scholars have enhanced GrabCut for more precise pattern extraction. The improvements include integrating segmentation with multiscale feature extraction [17], combining color correction with interactive GrabCut for efficiency [18], and merging deep image processing with object segmentation and model building [19]. GrabCut effectively extracts features of Zhuang brocade patterns, with interactive algorithms compensating for detail omissions in the extraction process.…”

Section: Work Related To Pattern Extraction Algorithmsmentioning

confidence: 99%

Research on the Design of Zhuang Brocade Patterns Based on Automatic Pattern Generation

Ni,

Huang,

et al. 2024

Applied Sciences

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To promote the inheritance of Zhuang brocade culture and the rapid extraction of features and automatic generation of patterns, this paper constructs a feature dataset of Zhuang brocade patterns and proposes an automatic generation technology using relative coordinates and regional content replacement. Firstly, by sorting through a large number of cases, a feature dataset of Zhuang brocade patterns is constructed. For the significant features of Zhuang brocade patterns, intelligent extraction algorithms and processes are used to effectively extract the color matching, patterns, and organizational forms of the patterns into the feature dataset. Secondly, to generate Zhuang brocade patterns quickly, an automatic generation technology based on genotype encoding and regional replacement algorithms is proposed, which encodes these pattern elements into a format that can be interpreted by computer algorithms. Finally, through similarity evaluation, the method’s feasibility for rapid extraction and generation of Zhuang brocade patterns is effectively verified. This method is significant for the inheritance of Zhuang brocade patterns and the development of the intangible cultural heritage industry.

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“…Underwater image enhancement in the recent decade attained great popularity in processing images and underwater vision [1]. It is hard to enhance an underwater image because of the typical underwater conditions and lighting effects [2], [3]. The color distortion influences underwater situations, and contrast degrades because of absorption [4].…”

Section: Introductionmentioning

confidence: 99%

Multi-scale fusion for underwater image enhancement using multi-layer perceptron

Sudhakara

Meena

2021

IJ-AI

Self Cite

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<span id="docs-internal-guid-54b35aa6-7fff-0992-ed4c-aca4d05cfcfa"><span>Underwater image enhancement (UIE) is an imperative computer vision activity with many applications and different strategies proposed in recent years. Underwater images are firmly low in quality by a mixture of noise, wavelength dependency, and light attenuation. This paper depicts an effective strategy to improve the quality of degraded underwater images. Existing methods for dehazing in the literature considering dark channel prior utilize two separate phases for evaluating the transmission map (i.e., transmission estimation and transmission refinement). Accurate restoration is not possible with these methods and takes more computational time. A proposed three-step method is an imaging approach that does not need particular hardware or underwater conditions. First, we utilize the multi-layer perceptron (MLP) to comprehensively evaluate transmission maps by base channel, followed by contrast enhancement. Furthermore, a gamma-adjusted version of the MLP recovered image is derived. Finally, the multi-scale fusion method was applied to two attained images. The standardized weight is computed for the two images with three different weights in the fusion process. The quantitative results show that significantly our approach gives the better result with the difference of 0.536, 2.185, and 1.272 for PCQI, UCIQE, and UIQM metrics, respectively, on a single underwater image benchmark dataset. The qualitative results also give better results compared with the state-of-the-art techniques.</span></span>

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An efficient interactive segmentation algorithm using color correction for underwater images

Cited by 6 publications

References 12 publications

A Mirror-Based Active Vision System for Underwater Robots: From the Design to Active Object Tracking Application

A Mirror-Based Active Vision System for Underwater Robots: From the Design to Active Object Tracking Application

Research on the Design of Zhuang Brocade Patterns Based on Automatic Pattern Generation

Multi-scale fusion for underwater image enhancement using multi-layer perceptron

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