New method for the fusion of complementary information from infrared and visual images for object detection

Visual and infrared cameras have complementary properties and using them together may increase the performance of object detection applications. Although the fusion of visual and infrared information results in a better recall rate than using only one of those domains, there is always a decrease in the precision rate whereas the infrared domain on its own always has higher precision. Thus, the fusion of these domains is meaningful only for a better recall rate, which means that more foreground pixels are detected correctly. This study presents a new computationally more efficient and simpler method for extracting the complementary information from both domains and fusing them to obtain better recall rates than those previously achieved. The method has been tested using a well-known database and a database created for the study and compared with earlier fusion methods.


Using multi-modal 3D contours and their relations for vision and robotics
BAŞESKİ, Emre; Pugeault, Nicolas; Kalkan, Sinan; BODENHAGEN, Leon; Piater, Justus H.; KRÜGER, Norbert (Elsevier BV, 2010-11-01)
In this work, we make use of 3D contours and relations between them (namely, coplanarity, cocolority, distance and angle) for four different applications in the area of computer vision and vision-based robotics. Our multi-modal contour representation covers both geometric and appearance information. We show the potential of reasoning with global entities in the context of visual scene analysis for driver assistance, depth prediction, robotic grasping and grasp learning. We argue that, such 3D global reasoni...
A tracker-aware detector threshold optimization formulation for tracking maneuvering targets in clutter
Aslan, Murat Samil; Saranlı, Afşar (Elsevier BV, 2011-09-01)
In this paper, we consider a tracker-aware radar detector threshold optimization formulation for tracking maneuvering targets in clutter. The formulation results in an online method with improved transient performance. In our earlier works, the problem was considered in the context of the probabilistic data association filter (PDAF) for non-maneuvering targets. In the present study, we extend the ideas in the PDAF formulation to the multiple model (MM) filtering structures which use PDAFs as modules. Althou...
Comments on "Detection of signals of unknown duration by multiple energy detectors"
SİPAHİGİL, OKTAY; Çiloğlu, Tolga (Elsevier BV, 2014-01-01)
In the 2010 paper entitled "Detection of signals of unknown duration by multiple energy detectors", a procedure to detect signals of unknown duration under Gaussian noise has been proposed and probability of detection and probability of false alarm expressions have been derived. This note indicates an error made at the beginning of these derivations.
FPGA-based infrared image deblurring using angular position of IR detector
Doner, Tugay; GÖKCEN, DİNÇER (Springer Science and Business Media LLC, 2020-08-01)
The motion of the object or the infrared (IR) imaging system during the integration time causes blurring of the IR image. This study covers real-time field programmable gate array (FPGA)-based deblurring for IR detectors, and an inertial measurement unit (IMU) was used to quantify the blur caused by the IR detector movement. Point spread function for each pixel was calculated using the angular position data of the IR detector obtained from IMU. Both spatially invariant and spatially variant blur cases can b...
Automatic segmentation of VHR images using type information of local structures acquired by mathematical morphology
AYTEKİN, orsan; Ulusoy, İlkay (Elsevier BV, 2011-10-01)
The morphological profile (MP) and differential morphological profile (DMP) have been used extensively to acquire spatial information to be used in the segmentation of very high resolution (VHR) remotely sensed images. In most of the previous approaches, the maxima of the MP and DMP were investigated to estimate the best representative scale in the spatial domain for the pixel under consideration. Then, the object type (i.e. dark, bright or flat) was estimated based on the location of the maximum. Finally, ...
Citation Formats
İ. Ulusoy, “New method for the fusion of complementary information from infrared and visual images for object detection,” IET IMAGE PROCESSING, pp. 36–48, 2011, Accessed: 00, 2020. [Online]. Available: