Holistic and component plant phenotyping using temporal image sequence

Image Sharpening Using Image Sequence and Independent Component Analysis

The novel approach to the image sharpening problem is proposed in this paper. It is based on the application of the independent component analysis (ICA) algorithm on the image sequence with the appropriate time displacement between the image frames. The novelty is in the data representation required by the ICA algorithms where each selected image frame has been used as a sensor implying that un...

Image-based phenotyping of plant disease symptoms

Plant diseases cause significant reductions in agricultural productivity worldwide. Disease symptoms have deleterious effects on the growth and development of crop plants, limiting yields and making agricultural products unfit for consumption. For many plant-pathogen systems, we lack knowledge of the physiological mechanisms that link pathogen infection and the production of disease symptoms in...

Image-based Plant Disease Phenotyping 2

Face Recognition Using Temporal Image Sequence

We present a face recognition method using image sequence. As input we utilize plural face images rather than a `single-shot', so that the input re ects variation of facial expression and face direction. For the identi cation of the face, we essentially form a subspace with the image sequence and apply the Mutual Subspace Method in which the similarity is de ned by the angle between the subspac...

Image-based plant phenotyping with incremental learning and active contours

Plant phenotyping investigates how a plant’s genome, interacting with the environment, affects the observable traits of a plant (phenome). It is becoming increasingly important in our quest towards efficient and sustainable agriculture. While sequencing the genome is becoming increasingly efficient, acquiring phenotype information has remained largely of low throughput. Current solutions for au...