A Review of ROI Image Retrieval Techniques

Shrivastava, Nishant; Tyagi, Vipin

doi:10.1007/978-3-319-12012-6_56

Cited by 26 publications

(7 citation statements)

References 33 publications

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“…After reselected, every 30,000 workpieces updated the parameters of the model, and executed continuous fine-tune. When the training sets expansion up to 120,000, the elbow method [30] happened, so we extracted the model as the final version of the network. Then 30,000 reselected workpieces combined with an original 90,000 workpiece into 120,000 new dataset, among which the trained dataset accounted for 70% and the test dataset for 30% .…”

Section: Methodology Of the System Implementmentioning

confidence: 99%

“…In this work, the simple linear iterative clustering (SLIC) head was proposed to augment the mask area in the fully convolutional networks (FCN) branch [29] of the mask region-based convolutional neural network (R-CNN) [22] and coordinate the predicted score through ROI features [30,31]. The content of the predicted mask is divided into many cell regions with different degrees of overlap, which will complement each other with the ground truth.…”

Section: Introductionmentioning

confidence: 99%

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An Industrial Micro-Defect Diagnosis System via Intelligent Segmentation Region

Xia

Wang

Feng

2019

Sensors

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In the field of machine vision defect detection for a micro workpiece, it is very important to make the neural network realize the integrity of the mask in analyte segmentation regions. In the process of the recognition of small workpieces, fatal defects are always contained in borderline areas that are difficult to demarcate. The non-maximum suppression (NMS) of intersection over union (IOU) will lose crucial texture information especially in the clutter and occlusion detection areas. In this paper, simple linear iterative clustering (SLIC) is used to augment the mask as well as calibrate the score of the mask. We propose an SLIC head of object instance segmentation in proposal regions (Mask R-CNN) containing a network block to learn the quality of the predict masks. It is found that parallel K-means in the limited region mechanism in the SLIC head improved the confidence of the mask score, in the context of our workpiece. A continuous fine-tune mechanism was utilized to continuously improve the model robustness in a large-scale production line. We established a detection system, which included an optical fiber locator, telecentric lens system, matrix stereoscopic light, a rotating platform, and a neural network with an SLIC head. The accuracy of defect detection is effectively improved for micro workpieces with clutter and borderline areas.

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Section: Methodology Of the System Implementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Industrial Micro-Defect Diagnosis System via Intelligent Segmentation Region

Xia

Wang

Feng

2019

Sensors

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“…The background of the image contains unnecessary data that may affect the process of color analysis [31]. To return the user's detailed interest, a region-based feature is preferred which is largely dependent on segmentation techniques [32]. Image segmentation is the process where each pixel is assigned with a label, where pixels with the same label have the same characteristics [31].…”

Section: Pre-processing Of Imagementioning

confidence: 99%

Pineapple maturity classifier using image processing and fuzzy logic

Arboleda

Jesus

Tia

2021

IJ-AI

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This paper describes the development of a prototype using an image processing system for extracting features and fuzzy logic for classifying the maturity of pineapple fruits depending on the colors of its scales. The standards that the system used are from Philippine National Standards for fresh fruits-pineapple for the 'queen' variant. The prototype automatically classified the maturity of queen pineapple variant grown in Munting Ilog, Silang, Cavite, Philippines. Data gathered are from the images loaded into the system using a camera unit under a controlled environment. The images loaded consist of the three faces of the pineapple sample, each with 120-degree coverage to capture the whole 360-degree view of the scale. The images then are sent to the system of the prototype where the features of the images are segmented based on the RGB color reduction. By using the fuzzy logic classifier, the obtained experimental results showed 100% accuracy for both the unripe and overripe maturity and 90% accuracy for the under-ripe and ripe maturity classification. The results obtained show that the developed image processing algorithm and the fuzzy-logic-based classifier could be used as an accurate and effective tool in classifying the maturity of pineapples.

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“…It is crucial in the context of MOS, which are characterized by high morphological and contextual variability [23][24][25]. Some examples of techniques and tools for region retrieval from images can be found in [26][27][28][29].…”

Section: Related Workmentioning

confidence: 99%

Extraction of Knowledge Rules for the Retrieval of Mesoscale Oceanic Structures in Ocean Satellite Images

Vidal-Fernandez

Almendros-Jiménez

Piedra

et al. 2016

Hybrid Soft Computing for Image Segmentation

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The processing of ocean satellite images has as goal the detection of phenomena related with ocean dynamics. In this context, Mesoscale Oceanic Structures (MOS) play an essential role. In this chapter we will present the tool developed in our group in order to extract knowledge rules for the retrieval of MOS in ocean satellite images. We will describe the implementation of the tool: the workflow associated with the tool, the user interface, the class structure, and the database of the tool. Additionally, the experimental results obtained with the tool in terms of fuzzy knowledge rules as well as labeled structures with these rules are shown. These results have been obtained with the tool analyzing chlorophyll and temperature images of the Canary Islands and North West African coast captured by the SeaWiFS and MODIS-Aqua sensors.

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A Review of ROI Image Retrieval Techniques

Cited by 26 publications

References 33 publications

An Industrial Micro-Defect Diagnosis System via Intelligent Segmentation Region

An Industrial Micro-Defect Diagnosis System via Intelligent Segmentation Region

Pineapple maturity classifier using image processing and fuzzy logic

Extraction of Knowledge Rules for the Retrieval of Mesoscale Oceanic Structures in Ocean Satellite Images

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