Publications

@article{fernandez-robles_object_2016,

title = {Object recognition techniques in real applications},

author = {Laura Fernández-Robles},

url = {https://research.rug.nl/en/publications/object-recognition-techniques-in-real-applications},

year  = {2016},

date = {2016-01-01},

abstract = {This doctoral thesis presents object description and retrieval techniques applied to three different fields: boar spermatozoa classification based on acrosome integrity, tool wear monitoring in machining processes, and specific object detection in images to combat child sexual exploitation. The research develops new methods and descriptors, highlighting the creation of the colour COSFIRE filter, which enhances color description and object discrimination while maintaining background invariance.},

keywords = {Computer vision, image processing, machine learning, object recognition},

pubstate = {published},

tppubtype = {article}

}

@article{fernandez-robles_evaluation_2015,

title = {Evaluation of clustering configurations for object retrieval using sift features},

author = {Laura Fernández-Robles and Manuel Castejón-Limas and Javier Alfonso-Cendón and Enrique Alegre},

url = {https://link.springer.com/chapter/10.1007/978-3-319-12754-5_21},

year  = {2015},

date = {2015-01-01},

journal = {Project Management and Engineering: Selected Papers from the 17th International AEIPRO Congress held in Logroño, Spain, in 2013},

pages = {279–291},

abstract = {SIFT (Scale-Invariant Feature Transform) is a widely used keypoint descriptor for robust image matching and object recognition. It identifies distinctive features and matches them using a nearest-neighbor algorithm, followed by clustering with a Hough transform and pose verification via least-squares. However, the clustering choice lacks theoretical justification. This study explores and evaluates alternative clustering configurations based on keypoint pose parameters (x, y location, scale, and orientation).},

note = {Publisher: Springer International Publishing},

keywords = {ASASEC, Clustering, object recognition, SIFT},

pubstate = {published},

tppubtype = {article}

}