TY - GEN
T1 - Modified dendrite morphological neural network applied to 3D object recognition on RGB-D data
AU - Sossa, Humberto
AU - Guevara, Elizabeth
PY - 2013
Y1 - 2013
N2 - In this paper a modified dendrite morphological neural network (DMNN) is applied for 3D object recognition. For feature extraction, shape and color information were used. The first two Hu's moment invariants are calculated based on 2D grayscale images, and color attributes were obtained converting the RGB (Red, Green, Blue) image to the HSI (Hue, Saturation, Intensity) color space. For testing, a controlled lab color image database and a real image dataset were considered. The problem with the real image dataset, without controlling light conditions, is that objects are difficult to segment using only color information; for tackling this problem the Depth data provided by the Microsoft Kinect for Windows sensor was used. A comparative analysis of the proposed method with a MLP (Multilayer Perceptron) and SVM (Support Vector Machine) is presented and the results reveal the advantages of the modified DMNN.
AB - In this paper a modified dendrite morphological neural network (DMNN) is applied for 3D object recognition. For feature extraction, shape and color information were used. The first two Hu's moment invariants are calculated based on 2D grayscale images, and color attributes were obtained converting the RGB (Red, Green, Blue) image to the HSI (Hue, Saturation, Intensity) color space. For testing, a controlled lab color image database and a real image dataset were considered. The problem with the real image dataset, without controlling light conditions, is that objects are difficult to segment using only color information; for tackling this problem the Depth data provided by the Microsoft Kinect for Windows sensor was used. A comparative analysis of the proposed method with a MLP (Multilayer Perceptron) and SVM (Support Vector Machine) is presented and the results reveal the advantages of the modified DMNN.
KW - 3D object recognition
KW - Dendrite morphological neural network
KW - Kinect
KW - classification
KW - color
KW - depth segmentation
UR - http://www.scopus.com/inward/record.url?scp=84884964575&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-40846-5_31
DO - 10.1007/978-3-642-40846-5_31
M3 - Contribución a la conferencia
SN - 9783642408458
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 304
EP - 313
BT - Hybrid Artificial Intelligent Systems - 8th International Conference, HAIS 2013, Proceedings
T2 - 8th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2013
Y2 - 11 September 2013 through 13 September 2013
ER -