Acrosome integrity assessment of boar spermatozoa images using an early fusion of texture and contour descriptors

García-Olalla, Oscar; Alegre, Enrique; Fernández-Robles, Laura; Malm, Patrik; Bengtsson, Ewert

doi:10.1016/j.cmpb.2015.03.005

Cited by 18 publications

(3 citation statements)

References 30 publications

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“…In order to characterize the tool wear, we propose to use shape descriptors computed from the tool image. In particular, the combination of global and local shape descriptors is considered to be quite reliable and has been extensively applied lately [18,19,20]. On the one hand, local descriptors are used to characterize small patches of the image.…”

Section: The B-orchiz Proposal For Shape Descriptionmentioning

confidence: 99%

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A computer vision approach to analyze and classify tool wear level in milling processes using shape descriptors and machine learning techniques

García-Ordás

Alegre

González-Castro

et al. 2016

Int J Adv Manuf Technol

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In this paper we present a new approach to categorize the wear of cutting tools used in edge profile milling processes. It is based on machine learning and computer vision techniques, specifically using B-ORCHIZ, a novel shape based descriptor computed from the wear region image. A new Insert dataset with 212 images of tool wear has been created to evaluate our approach. It contains two subsets: one with images of the main cutting edge, and the other one with the edges that converge to it (called Insert-C and Insert-I, respectively). The experiments were conducted trying to discriminate between two (Low-High) and three (Low-Medium-High) different wear levels and the classification stage was carried out using a Support Vector Machine (SVM). Results show that B-ORCHIZ outperforms other shape descriptors (aZIBO and ZMEG) achieving accuracy values between 80.24% and 88.46% in the different scenarios evaluated. Moreover, a hierarchical cluster analysis was performed, offering prototype images for wear levels, which may help researchers and technicians to understand how the wear process evolves. These results show a very promising opportunity for wear monitoring automation in edge profile milling processes.

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Section: The B-orchiz Proposal For Shape Descriptionmentioning

confidence: 99%

“…In this paper we present B-ORCHIZ, a new shape descriptor based on the boundary point description. This method combines global and local shape descriptors, which improves the characterization of the images [18,19,20]. We evaluate it on an image-based tool wear monitoring system for edge profile milling.…”

Section: Introductionmentioning

confidence: 99%

A computer vision approach to analyze and classify tool wear level in milling processes using shape descriptors and machine learning techniques

García-Ordás

Alegre

González-Castro

et al. 2016

Int J Adv Manuf Technol

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“…In the following, we briefly review the most recent results related with our work for each of the three applications presented. Works dealing with the classification of the acrosome integrity of boar spermatozoa are mainly based on texture description [7]. In this work, we use an invariant local features approach based on the detection and description of keypoints.…”

Section: Introductionmentioning

confidence: 99%

Recognition and retrieval of objects in diverse applications

Fernández-Robles

2018

ELCVIA

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This work proposes and evaluates object description and retrieval techniques in different real applications. It addresses the classification of boar spermatozoa according to acrosome integrity using several methods based on invariant local features. In addition, it provides two new methods for insert localisation and an automatic solution for the recognition of broken inserts in edge profile milling heads that can be set up in-process without delaying any machining operations. Finally, it evaluates different clusterings of keypoints for object retrieval and proposes a new descriptor, named colour COSFIRE, in the scope of the European project Advisory System Against Sexual Exploitation of Children.

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